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Even with the Internet's ubiquitous distribution, close-to-unlimited inventory and easy duplication of media, Blip believes that rules of property still apply.
Unauthorized distribution of someone else's content is theft. High-tech theft is just as wrong, both legally and morally, as low-tech theft. We police our site just like retailers police their stores, and we don't tolerate theft.
Our producers work hard giving voice to their creativity in video, and we won't let anyone rob them of their effort. We also won't tolerate robbers showing their merchandise on our site.
We are fans of "copyleft" licenses such as those offered by Creative Commons. We encourage everyone to look into Creative Commons licenses and adopt them. Every video released under a copyleft license enriches the (lowercase) creative commons in a significant way.
We will not traffic in pornography. Blip is a place for series about ideas and entertainment. We want everyone to feel comfortable coming to our site and having their children and grandparents check it out as well. We're proud to be a venue for series that is well-lit, bright, organized and clean, and we are dedicated to keeping Blip exactly this way.
We believe that producers and viewers are stakeholders in Blip as much as our employees, founders and shareholders. Blip was designed, and continues to evolve, with the goal of serving each of these communities. We make every effort to develop tools, technologies and environments that these communities can take pride in and find useful.
We are dedicated to maintaining an excellent relationship with producer and viewer communities and their individual members, whether or not they are Blip users. We make every effort to participate in community forums and to be helpful in every way possible to members of the community.
The original Blip was designed based on direct interaction with the videoblogging community. We continue to be grateful to this community and to seek advice from its members, even as the community has evolved and grown over the years. We still get great advice from producers and viewers at BBQs across the country and get-togethers around the world, and we're always open to making changes based on community feedback. At Blip, we see software development as a collaborative effort between our company and the communities it serves.
We live in an age characterized by the democratization of expression.
We love that professional and up-and-coming independent producers can create entertaining series and gain audiences of millions. We celebrate that they can produce original series as their full time job and make hundreds of thousands of dollars a year, or more. Their only constraint is the limit of human creativity.
We believe that this liberation of the means of production is one of the most important things to happen in recent history. It allows anyone to create the next great sitcom or to share the reality of daily life across cultural boundaries. This is a beautiful thing, and we are dedicated to furthering this democratization in a way that respects intellectual property rights and in a venue where everyone feels comfortable.
We live in an economy of plenty. We believe it is in the interests of the community and in the interests of Blip to be open with media and with data about media. At Blip we are not building a walled garden but instead are actively working to break down walls to enable the free and open sharing of media and metadata throughout the Web.


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EMW thus far has completed their first and second E46 prototypes. These are some bold claims to be making without a kit available for sale and no measured performance numbers to substantiate the claims:
We hope they are able to come to market with a reliable, affordable, and superior performing electric solution that puts BMW's own to shame. However, can a company with no track record really beat some of the best engineers in the world with far greater resources at their disposal? Time will tell.

subset: commoncrawl


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CHATTANOOGA, Tenn. --- University of Tennessee at Chattanooga sophomores Hannah Wyatt (Soddy Daisy, Tenn.) and Logan Higgins (Louisville, Ky.) were selected preseason All-Conference by College Sports Madness for the Southern Conference.
Wyatt led Chattanooga with five assists last season and was ranked fifth in the league. She was second on the team in scoring last season with seven points. She recorded her first collegiate goal in the season opener against Tennessee Temple which proved to be the game winner. Higgins scored her first collegiate goal in Chattanooga's 2-2 tie at Lipscomb last season and recorded an assist against the Crusaders to start the year.
The Mocs, picked 11th in the Southern Conference preseason poll released Thursday, open the season Friday, August 23 at home against instate foe Austin Peay. The game kicks off at 7 p.m. and the gates open one hour prior to game time. Admission is free and concessions will be available.
Offensive Player of the Year Defensive Player of the Year
Stephanie DeVita, Furman Rose Hull, Furman
Freshman of the Year Coach of the Year
Malcaniesha Kelley, Samford Andrew Burr, Furman
First Team Second Team
F Julia Holz, Appalachian State F Chesney White, UNCG
F Brittany Hoffman, Samford F Emily Bougas, Wofford
F Stephanie DeVita, Furman F Nora El-Shami, Georgia Southern
F Markie-Lynn Studnicky, Western Carolina F Stephanie Piperno, Davidson
M Michelle Moll, Samford M Ana Mesa, The Citadel
M India Robinson, Furman M Maureen Buff, Wofford
M Mariana Garcia, The Citadel M Olivia Mackey, Elon
M Trine Taule, Samford M Hannah Wyatt, Chattanooga
D Hannah Stanifer, Furman D Logan Higgins, Chattanooga
D Lauren Lover, UNCG D Nicole Steyl, Appalachian State
D Ali Simpson, Furman D Renee Nance, Georgia Southern
D Alyssa Althoff, Furman D Jennifer McGorty, Elon
GK Rose Hull, Furman GK Jamie Simmons, UNCG


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Under Construction: Carman Hall Entrance
May 27, 2015
From June 2 to August 14, Carman Hall entrance will be located on 114th Street, east of Broadway.
Ruggles Wins 2015 Energy Challenge
April 09, 2015
The 2015 Energy Challenge has come to a close. Congratulations to Ruggles Hall – the winning building with a 15% reduction in electricity usage—way to go! Woodbridge and River... more
2015 Energy Challenge
March 30, 2015
Residence Hall Energy Challenge Begins March 26From March 26 – April 9, Columbia's undergraduate residential community† is invited to commit to the... more
Download the Columbia Housing App!
December 09, 2014
Columbia Housing is pleased to announce the launch of its new Guidebook app. If you downloaded the Housing Check-In Guidebook, you used it as a resource for information about... more


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According to reports provided by the Aiken Department of Public Safety:
An Aiken man reported on Wednesday that someone took an air compressor and a pressure washer from his home on Fairway Ridge.
An Aiken man reported on Tuesday that someone removed a wheel from his vehicle while it was parked on Churchill Circle.
He found the vehicle resting on a cement block.
Multiple broken windows were reported at a business on Richland Avenue on Tuesday.
A vehicle break-in was reported on Summerwood Way on Tuesday. The owner reported a front window had been smashed and a purse was missing.
According to reports provided by the Aiken County Sheriff's Office:
An Aiken man reported on Tuesday that someone syphoned about 60 gallons of diesel fuel from his trackhoe.
A Warrenville man reported a gun missing from the shed of his Glenwood Drive home on Tuesday.
A burglary was reported at a home on Lawana Drive in Gloverville on Monday. The owner reported firearms missing.
A burglary was reported on University Parkway
An additional burglary was reported on Old Camplong Road in Aiken.
Vehicle break-ins were reported on Golf Course Road in Warrenville and White Ash Street in Warrenville
A vehicle break-in was reported on Jefferson Davis Highway in Beech Island.
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Search by campus:
The Kent State University Regional Campuses advance Northeast Ohio by providing open access to a major University education. The Campuses are key intellectual resources for social diversity, cultural enhancement, and economic development.
Copyright 2015 Kent State University 3300 Lake Road West Ashtabula, OH 44004 Phone: 440-964-3322 Class Cancellations: 440-964-4395


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Mey House is perfectly located for those visiting Orkney and The Castle of Mey. The generously proportioned suites all have panoramic ocean views, feature super king-sized beds, separate dressing area...More about Mey House Luxury Rooms and Breakfast
Currently the rating for this establishment is not confirmed. This may be due to a change of ownership or because it has only recently joined the AA rating scheme ...More about The Creel Restaurant with Rooms
This delightful country house is set in its own 20 acres of woodland and was originally built in 1810. The hotel offers a choice of bedrooms from the traditional styled rooms in the main house to the...More about Forss House Hotel
This well-established hotel is situated just outside the town centre overlooking the River Wick, and enjoys an entrance on to the world's shortest street; Ebenezer Place. MacKay's provides well-equipp...More about Mackay's Hotel


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Playboy: Complete this sentence: "Reading is …." Sarah: Sexy! Playboy: We're so glad you didn't say "fundamental." So what makes reading so sensual? Sarah: There's such an intimate connection between you and a book. What's sexier than being able to say you've read Herma...
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text: Taking Control of Blood Sugars at School By Janet Sirstins, RN, CDE November 26, 2014 Parents of children with Type 1 and Type 2 Diabetes, as well as high school and college students with Type 1 and Type 2 Diabetes, often struggle with control of their Blood Sugars during class-time. Here are some tips. Read More


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|Home » News » 2012 News Archive
|Monday, August 3, 2015
First Nations Payments Systems and ISC Network partner to bring fastball fans 24 games in full High Definition from the 2015 ISC World Tournament
Thursday, July 30, 2015
South Bend, IN
Wednesday, July 29, 2015
South Bend, IN
Thursday, July 16, 2015
South Bend, IN
Tuesday, July 14, 2015
Findlay, OH
Tuesday, July 14, 2015
South Bend, IN
11-23-12 Hackettball Photography Update
Friday, November 23, 2012
2012 ISC World Tournament, Day 1 Album (542 photos)
2012 ISC World Tournament, Day 2 Album (531 photos)
2012 ISC World Tournament, Day 3 Album (549 photos)
2012 ISC World Tournament, Day 4 Album (826 photos)
2012 ISC World Tournament, Day 5 Album (749 photos)
2012 ISC World Tournament, Day 6 Album (1,000 photos)
2012 ISC World Tournament, Day 6 Album 2 (118 photos)
2012 ISC World Tournament, Day 7 Album (1,000 photos)
2012 ISC World Tournament, Day 7 Album 2 (441 photos)
2012 ISC World Tournament, Day 8 Album (60 photos)
2012 ISC World Tournament, ISC II Awards Album (122 photos)
2012 ISC Hall of Fame Breakfast Album (49 photos)
2012 ISC World Tournament Team Photos (44 photos)
2012 ISC World Tournament Opening Ceremonies (180 photos)
(11-23-12) Note: First 7 days of game action photos are now posted, currently working on the 8th and final days photos.
Now up to: 6,211 photos posted and counting!
Each of the photos of the album are low resolution examples with a watermark attached, to give the viewers and idea of what we have taken. When the photos are purchased, the watermark is removed, the ISC World Tournament logo is added, and each photo will be high resolution.
For purchasing, here are the instructions:
1.You can use the paypal link attached to the above website address. When ordering the individual photos, after purchasing, please email me (firstname.lastname@example.com) what photos, from which album you would like (Example: You order one photo, and you email me "I would like #57 of ISC Day 1"). Please use a headline of ISC Photos when emailing me so I don't miss it.
2.For others that don't use paypal, you can send me a check, cash, or money order made out to: Bruce Hackett to the following address:
Bruce Hackett
82 Rodaha Drive
Corning, NY 14830
3. If you use a non pay pal form of purchasing photos, please send me an email letting me know so that I can work on your photo and once payment is received you can be sent your order.
4. Please note, once you purchase individual photos, you will be emailed the photos that you purchase. These photos will not be printed and mailed to you. Instead you will be emailed the photos so that you have the digital image to keep, and can make as many copies as you wish.
5. Anyone purchasing the Team photo, or single game, or team packages: All of your team's images for the package you purchase will be included on the DVD in folders. All images will be high resolution photos with the ISC Logo attached to each of the photos. These DVD's will be mailed to you once they are completed.
Most of the photo examples we have in the galleries are either in 5x7 or 8x10 format. These are the two formats that work best for displaying the images.
Finally I would like to point out to everyone, that this has been a major undertaking for us, and that we both have normal jobs that do not include photography, so we will be conducting work on the photos each night after the work day ends, so it may take us awhile to get the photos done, but rest assured we will put in the time to get the photos done and out to view as quickly as we possibly can.
Bruce Hackett & Meshion McDaniels
Hackettball Photography
Hackettball Photography: http://hackettball.sharepoint.com/Pages/2012ISCPhotography.aspx
Hackettball Photography Facebook Page: http://www.facebook.com/HackettballPhotography
Email Contact: firstname.lastname@example.com
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Courses: General Chemistry I (CHEMB10300C)
Fall 2012
Class Number: 1168
For students with some background in chemistry. Sections usually have a maximum of 55 students. Topics include aqueous solutions and solubility; the electronic structure of atoms and molecules; chemical reactions and energy; intermolecular forces. Examples discussed in lecture and laboratory workshop include environmental sciences, material sciences and biological chemistry. Lecture three hours and Chemistry workshop three hours a week. The laboratory workshop period will be used for traditional chemical experimentation or related problem solving. The course may include individual conferences, evening problem or peer-led instruction sessions. Pre-requisites: Satisfactory performances on the Chemistry Placement Test and on the Quantitative Reasoning Assessment.
Div: IIL and Q; Approach: Scientific Investigation (SI), Quantitative Readiness Required (QR), Quantitative Methods (QM); Haverford: Natural Science and Quantitative (NA/QU)
Fulfills: Class Nbr: 1168 Div: IIL and Q; SI;QR;QM;
Bryn Mawr, PK278,PK182
Meeting Times
W 1:00pm-4:00pm,W 2:00pm-4:00pm


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CHATTANOOGA, Tenn. --- Junior Keon Williams (Chattanooga) scored three times to power the Chattanooga Mocs (2-1) to a 42-10 win over visiting Austin Peay (0-3) in Finley Stadium Saturday night. Williams posted his second straight 100-yard rushing night while the UTC defense had a stout effort in the runaway win.
Williams carried the ball 11 times for 106 yards, an average of 9.6 yards per carry, to pace a Mocs rushing attack that accounted for 270 of the offense's 412 yards. His three scores came from nine, one and 25 yards.
"I thought Keon Williams was unbelievable," Head Coach Russ Huesman said. "He's running hard. I think we are all seeing it. He's running, breaking tackles and making people miss. If he can continue to work, the sky is the limit right now."
The defense was just as impressive. The Governors had 141 yards on 27 plays on their two scoring drives. The other 10 drives amounted to a mere 69 yards on 37 plays (1.87 yards) including six three-and-outs.
The offense was spectacular to open the contest for the second consecutive week. It scored on drives of 76, 61 and 60 yards en route to a 35-7 halftime advantage. The Mocs shared the wealth, with the opening score coming from Marquis Green (Palmetto, Fla.) on a nine-yard run. Six minutes later Williams scored from nine yards out to make it 14-0.
Tim Phillips got Austin Peay on the board with 1:41 to go in the first quarter. He bulled in from eight yards to make it a 14-7 contest. It was all Chattanooga from there.
Jacob Huesman (Chattanooga) found Terrell Robinson (South Pittsburg, Tenn.) for an eight-yard score. Williams plunged in from a yard out for the 28-7 lead. It looked like the offense was going to get its fifth scoring drive when Huesman was intercepted by Leron Eaddy at the Govs five with less than a minute go in the half.
Peay tried to mount an attack passing on the first play, but D.J. Key (Centerville, Tenn.) got a hand on the ball, deflecting it into the waiting arms of linebacker Gunner Miller (Chattanooga). Twenty yards later Miller scored his second career touchdown for a 35-7 halftime advantage. The 35 points is the highest first half total since scoring 42 against Mississippi Valley State on September 16, 2000.
Williams capped the Mocs scoring on UTC's first drive of the third quarter. He delivered a punishing 25-yard run to the end zone, making it 42-7. Walter Spears kicked a 26-yard field goal with 3:15 to go in the third to provide the 42-10 final.
Four Chattanooga runners accumulated at least 40 yards on the ground. Williams was joined by Tommy Hudson (Moultrie, Ga.), Kendrix Huitt (Atlanta, Ga.) and Huesman with 63, 47 and 40 yards, respectively. The Mocs averaged a strong 6.1 yards per carry on the night.
Huesman threw for another 142 yards, completing 15 of 20 with a touchdown and interception. Robinson was his favorite target with 53 yards on six catches.
Phillips gained 78 yards on 18 carries to lead the Govs offense. Andrew Spivey threw for 61 (7-17-1) before Jacob Sexton came off the bench to hit five of seven throws for 33 yards.
Chaz Moore (Memphis, Tenn.) and Muhasibi Wakeel (Decatur, Ga.) combined for a team-high seven stops. Moore had 1.5 tackles for loss and a pass breakup. Kadeem Wise (Lawrenceville, Ga.) added six tackles, one for loss, and two pass breakups.
Montez Carlton paced the Governors with eight tackles. Four others had seven, including Eaddy, whose interception thwarted a scoring drive.
The Mocs have a week off before returning to the field September 28 at Georgia Southern. Kickoff is slated for 6 p.m., in Statesboro.
Play - Quarter/Time/Score
UTC – Marquis Green 9 yard rush (Nick Pollard Kick) - 1/12:05/7-0
Drive: 8 plays, 76 yards, 2:55
Key Play(s): 2/2/H44 – Jacob Huesman to Faysal Shafaat for 25 yards
UTC – Keon Williams 9 yard rush (Pollard Kick) - 1/6:34/14-0
Drive: 8 plays, 61 yards, 3:46
Key Play(s): 3/7/V28 –Huesman to Shafaat for 19 yards. Great play on the ball by Shafaat.
APSU – Tim Phillips 8 yard rush (Walter Spears Kick) - 1/1:41/14-7
Drive: 12 plays, 79 yards, 4:49
Key Play(s): 4/8/H39 – Andrew Spivey 23 yards to Daryl Clack
UTC – Terrell Robinson 8 yard pass from Jacob Huesman (Pollard Kick) - 2/13:30/21-7
Drive: 7 plays, 60 yards, 2:58
Key Play(s): 4/1/H49 – Huesman 5 yard run
UTC – Williams 1 yard rush (Pollard Kick) - 2/3:12/28-7
Drive: 7 plays, 38 yards, 2:32
Key Play(s): 3/6/V17 – Huesman hits Troy Dye for 16 yards…Dye's 1st career catch
UTC – Gunner Miller 20 yard Interception Return (Pollard Kick) - 2/0:24/35-7
Drive: N/A
Key Play(s): N/A
UTC – Williams 25 yard Run (Pollard Kick) – 3/11:00/42-7
Drive: 5 plays, 51 yards, 2:18
Key Play(s): 2/9/50 – Tommy Hudson runs 21 yards
APSU – Spears 26 yard Field Goal – 3/3:15/42-10
Drive: 15 plays, 62 yards, 7:37
Key Play(s): 3/1/H35 – Jacob Sexton 2 yard run


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I have Arma Atari version and Queens Gambit from the GamersGate. When I click autorun, the splash has install and play greyed out and I can not go any further from there.
Ive tried to install on ARMA 1.08 (official patch download), ARMA 1.08 (patch from gamersgate install folder), and ARMA 1.14. All with no success.
There is no setup.exe in the installation folder and I would prefer not to manually install it.
Is there a solution to this?


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With Xbox Live Gold, you get the most advanced multiplayer, free games, exclusive member discounts up to 50-75% on games in the Xbox Store, and more. And on Xbox One, it's even better, with smarter, faster matchmaking, and online multiplayer for everyone in your home.*
Play games like Titanfall and Halo with your friends on a network powered by over 300,000 servers for maximum performance. Cloud-hosted multiplayer helps eliminate lag and cheating. And on Xbox One, find new challengers who fit your skill and style with Smart Match.*
Smart Match on Xbox One finds you new challengers who fit your skill and style, using intelligent algorithms. And the community-powered reputation systems helps identify cheats and annoying people to keep them out of your games.*
You no longer have to wait in lobbies while a match is found. Feel free to play a game, watch TV, or listen to music while we find your perfect match. Then you can jump in instantly.
Catch up on games you've always wanted to play with a growing library of free titles on Xbox One and Xbox 360.**
With Deals with Gold, you save up to 50-75% on games in the Xbox Store.
As a Gold member you get a membership area showcasing your free games**, monthly deals, and other great benefits. Check out the membership area now to see which free games and discounts are available for download now.
Xbox Live Gold gets you into the multiplayer arena, letting you broadcast your most epic multiplayer duels over Twitch. Join a broadcaster's game for a multiplayer showdown to prove that you are the best in the world.
Record your most epic multiplayer moments, effortlessly save them to the cloud, and use Upload Studio to personalize your clips and share with friends or on Twitter. You can also stay up-to-date with your friends' current activities with the new friends section. See the most popular games your friends are playing, and a Gamerscore leaderboard to see who has improved their Gamerscore over the last 30 days.
With Home Gold, on Xbox One, a single Gold membership provides multiplayer for everyone in your home.*
Share your free Games with Gold** games with everyone in your home. With Home Gold, everyone gets to play
Experience the world's best workouts with instant, personalized feedback, right in your home on Xbox Fitness.* Train with Jillian Michaels, Tracy Anderson, Tony Horton of P90X®, Shaun T of INSANITY®, and more. Optimize every workout with immediate feedback on your form, power, and heart rate on Xbox One with Kinect. Buy individual workouts, and get over 30 additional workouts for free with Xbox Live Gold. Only on Xbox One.***
|Xbox Live Gold
membership includes:
|Online Multiplayer
|Free Games with Games with Gold
|Exclusive Discounts with Deals with Gold
|Parties and Party Chat
|Smart Match
|Home Gold
|Game DVR Cloud Storage
|Upload Studio
|Xbox Fitness***
Play with friends on the most advanced multiplayer network, get free games, and receive exclusive discounts.Get Xbox Live Gold
*IMPORTANT! Xbox Live Gold no longer required for some apps and features, including Netflix, Twitch, ESPN, Skype, and YouTube. Some apps require app provider-specific subscriptions and/or other requirements. See xbox.com/livefaq. Home Gold: Limited to 1 Xbox One in home; restrictions apply. Smart Match matchmaking and Cloud Hosted Multiplayer available in supported games. Media content and games, including Titanfall and Halo sold separately. Halo Spartan Assault available now on Xbox 360 and Xbox One. Halo 5: Guardians coming 2015. Multiplayer between Xbox One and Xbox 360 not supported.
**Games with Gold Offer for paid Gold members only; Active Gold membership required to play downloaded Xbox One games. Each participating game (selected by Xbox) available for download from Xbox Store during specific window; available games may vary by country. Some titles may only be available for download by adult account holders 18+. Kinect and/or hard drive required for some games. Offer available in all Xbox Live countries where Xbox Live Gold memberships are supported. Offer is non-transferable, not redeemable for cash, and cannot be combined with any other rebate or offer. Offer terms and availability subject to change. Taxes, if any, are the sole responsibility of member. Download charges may apply as set by your ISP. For Xbox Live Terms of Use and system requirements, see xbox.com/live.
***Xbox One Kinect sensor (required) and Xbox Live Gold membership sold separately. For more information on additional workouts included with Xbox Live Gold see xbox.com/xboxfitness.
Game DVR and Upload Studio require Xbox Live Gold. Live TV Trending will initially be made available to preview users in the U.S., Canada and the UK. Twitter TV Trending will initially be made available to preview users in the U.S. Kinect for Xbox One required for some features. Games with Gold Free Games Offer for paid Gold members only. Active Gold membership required to play downloaded Xbox One games. Some restrictions apply. See xbox.com/live.


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20% Off Storewide! When you purchase a Buddy Rest bed, you can be certain you will receive the highest quality dog bed available today. We use advanced sleep science to improve the quality of life for pets. Our beds are the perfect blend of style, quality, and innovation. Only BuddyRest memory foam dog beds offer true arthritic relief, while also providing the unparalleled protection of Crypton smart fabrics. These orthopedic dog beds are recommended to give the best science of support, and to help treat and prevent canine arthritis. You can rest easy knowing that you invested in a product that was made with the highest quality craftsmanship, using the best materials and technology available today.
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text:
A high illiteracy rate in Haiti has contributed to a strong oral tradition. Elders pass their knowledge and wisdom to younger generations in the form of clever and poetic proverbs, as contained in this slideshow.
You can also watch Haitian proverbs on our Vimeo channel.
Watch a report about Haiti in Notes from the field.


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SUBSCRIBEWe will NOT sell your email address to anybody!
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text: Every year, VOP (Voices of Praise Gospel Choir) goes on a Spring Tour to praise and minister the word of God. This year we're going to Orlando, Florida and this is such an exciting time. Spring Break will be filled with fun, love praise and relaxation. Everyone has been preparing to represent God and BW right. VOP has been one of the greatest organizations I have been involved in. I have met many amazing people and I have strengthened my relationship with Christ since becoming a member of the choir. Only two more weeks until we hit the road to Florida!!


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Mixed Stripe High Low Maxi Dres
Style # 210644
- 96% rayon, 4% spandex
- Center back to hem: 55" (140 cm)
- Jersey lining
- Dry clean
- Imported
- Model is 5'9" and is wearing a US size S
Rated 5 out of 5Āby 2 reviewers.
Rated 5 out of 5Āby bebegirl19 Cute dress for summer This dress is super cute and fits perfect! It is the perfect spring into summer dress and can easily be dressed up or down with flats or heels. April 26, 2013
Rated 5 out of 5Āby islandamerican2 Fits true to size I had a baby six months ago and this dress looks amazing on me. I normally wear xs but size s fits perfect. I love the material and the length!!!! March 5, 2013
1-2 of 2


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Revision Information
- Reviewer: Michael Woods, MD
- Review Date: 12/2014 -
- Update Date: 12/20/2014 -
1599 Clifton Road
Atlanta, GA 30329
PO Box 102454
Atlanta, GA 30368-2454
The American Cancer Society provides information and support to patients and families through a network of local chapters. The society supports cancer-related research. It takes an active approach to teaching people ways to reduce the risk of developing cancer.
1311 Mamaroneck Ave.
White Plains, N.Y. 10605
The Leukemia & Lymphoma Society provides information and support to lymphoma and leukemia patients, family members, and caregivers. It offers family support groups in 230 communities across the United States and peer-to-peer telephone support for patients.
NCI Public Inquiries Office
6116 Executive Boulevard
Room 3036A
Bethesda, MD 20892-8322
The National Cancer Institute is part of the National Institutes of Health. It provides information about leukemia and other cancers. The Institute funds research related to cancer, and its website includes information about clinical trials.
Suite 200, 10 Alcorn Avenue
Toronto, Ontario M4V 3B1
(416) 961-7223
Our website provides cancer patients, their friends and family, and the general public with up-to-date information about cancer and cancer prevention.


text:
Using Your Gifts
In his correspondences with the various churches with which he interacted, the Apostle Paul is clear on the fact that God endows individuals within the body of Christ with skills and abilities for the purpose of edifying the whole body. …Read More
Vanity Fair
For John Bunyan, a Puritan to his fingertips, the Christian life was an experience of conflict and tension with this world. Imprisoned for upwards of twelve years, he experienced firsthand the world's hostility. Cheerful and sanguine by temperament, his portrayal …Read More
Vehicles for Giving the Self: An Interview with Michael Card
Tabletalk: Please tell us a little about the sort of ministry you are involved in these days. Michael Card: The ministry I am involved with these days is fundamentally the same one that's been going on for thirty years: trying …Read More
Virtual Friendship
Let's begin with a reasonably safe prediction: you are not likely to finish this article. That is not merely because of the prose of the author (though I concede it doesn't help). It is based on reliable statistics that indicate …Read More
Vital Members
I have often spoken out against all the pragmatic and "seeker-sensitive" approaches to contemporary worship because they tend to diminish the proper place of preaching and replace it with quasi-spiritual forms of sheer entertainment (music, comedy, drama, and whatnot). Any …Read More
Voices of Temptation
The birth of Ishmael, son of Abram and Hagar, is a tale that in some sense at least should never have been. From it emerges a familial and ethnic strife that lasts to this very day. It is a tale …Read More
Walking in Good Works
Ephesians 2 is filled with the good news of grace for both our justification and sanctification. The chapter begins by describing our natural condition—trapped in sin and by sin, rebelling against God to pursue our own ends on the one …Read More
War and Peace
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text:
The present invention provides systems and methods for obtaining a three-dimensional (3D) representation of one or more light sources inside a sample, such as a mammal. Mammalian tissue is a turbid medium, meaning that photons are both absorbed and scattered as they propagate through tissue. In the case where scattering is large compared with absorption, such as red to near-infrared light passing through tissue, the transport of light within the sample is described by diffusion theory. Using imaging data and computer-implemented photon diffusion models, embodiments of the present invention produce a 3D representation of the light sources inside a sample, such as a 3D location, size, and brightness of such light sources.
1. A method for obtaining a tree-dimensional representation of a light source distribution located inside a mammal, the method comprising:
capturing surface light image data for light emitted from a surface portion of a mammal and propagating from the light source distribution located inside the mammal to the surface portion;
obtaining a topographical surface representation of at least a portion of the mammal;
dividing the topographical surface representation into a set of surface elements;
creating a set of volume elements within the mammal, said set of volume elements relating to said set of surface elements;
converting the surface light image data into photon density just inside the surface of the mammal using the set of surface elements and the set of volume elements; and
constructing a three-dimensional representation of the light source distribution internal to the mammal with a processor using the photon density just inside the surface.
2. The method of
3. The method of
4. The method of
5. The method of
6. The method of
defining a cost function and a set of constraints for obtaining a solution for the three-dimensional representation of the light source distribution.
7. The method of
8. The method of
9. The method of
10. The method of
11. The method of
varying the number of surface elements to produce a set of solutions for the three-dimensional representation of the source distribution.
12. The method of
13. The method of
applying a noise threshold to the surface light image data.
14. The method of
placing the mammal on a stage included in an imaging chamber coupled to a camera configured to capture an image of the mammal on the stage.
15. The method of
moving the stage to one or more other positions in the imaging chamber, wherein the other positions have different angles relative to a fixed datum associated with the camera than the first position; and
capturing additional image sets of the mammal from the other positions using the camera.
16. The method of
17. A method for obtaining a three-dimensional representation of a light source distribution located inside a mammal, the method comprising:
capturing surface light image data for light emitted from a surface portion of a mammal, said light propagating from the light source distribution located inside the mammal to the surface portion;
converting the surface light image data into photon density just inside the surface of the mammal; and
constructing a three-dimensional representation of the light source distribution internal to the mammal with a processor using the photon density just inside the surface.
18. The method of
19. The method of
This application is a continuation of U.S. application Ser. No. 10/606,976 filed Jun. 25, 2003, which (1) claims priority under 35 U.S.C. �119(e) from U.S. Provisional Application No. 60/395,357 filed Jul. 16, 2002, (2) claims priority under 35 U.S.C. �119(e) from U.S. Provisional Application No. 60/396,458 filed Jul. 16, 2002, and (3) claims priority under 35 U.S.C. �119(e) from U.S. Provisional Application No. 60/396,313 filed Jul. 16, 2002; each of these patent applications is incorporated by reference in its entirety for all purposes.
The present invention relates generally to imaging with light. In particular, the present invention relates to systems and methods for obtaining a three-dimensional representation of a light source or light source distribution inside a turbid sample, which is particularly useful in biomedical imaging and research applications.
Bioluminescent imaging is a non-invasive technique for performing in vivo diagnostic studies on animal subjects in the areas of medical research, pathology and drug discovery and development. Bioluminescence is typically produced by cells that have been transfected with a luminescent reporter such as luciferase and can be used as a marker to differentiate a specific tissue type (e.g. a tumor), monitor physiological function, track the distribution of a therapeutic compound administered to the subject, or the progression of a disease. A wide range of applications have been demonstrated including areas of oncology, infectious disease, and transgenic animals. In vivo imaging of cells tagged with fluorescent reporters is a related technology that has also been demonstrated recently in both green fluorescent protein (GFP) and near infrared (NIR) dyes such as Cy5.5.
Photons emitted by bioluminescent cells are strongly scattered in the tissue of the subject such that propagation is diffusive in nature. As photons diffuse through tissue many are absorbed, but a fraction reach the surface of the subject and can be detected. In general, absorption in mammalian tissues is high in the blue-green part of the spectrum (<600 nm) and low in the red and NIR part of the spectrum (600-900 nm). Firefly luciferase has a rather broad emission spectrum ranging from 500-700 nm, so at least part of the emission is in the low absorption region. Since the mean-free-path for scattering in tissue is short, on the order of ˜0.5 mm, photons from deep sources are scattered many times before reaching the surface. Bioluminescent imaging systems effectively record the spatial distribution of these photons emitted from the surface of the subject.
However, the most important quantitative information is not directly related to the surface emission but instead pertains to the bioluminescent source inside the subject. Important parameters are the source strength (related to the number of light emitting cells), position and geometry. Most of the bioluminescent imaging work published to date involves use of single-view 2D imaging systems. Image analysis usually involves quantifying a light emitting region-of-interest (ROI) on the subject surface. While this analysis methodology is simple and provides a good relative measure of light emission, it does not take into account the source depth and resulting attenuation through tissue.
Hence, there is interest in developing both improved imaging systems and reconstruction algorithms that would provide the three-dimensional distribution of photon emission inside the sample (e.g., animal) from images measured on the sample surface.
The present invention provides systems and methods for obtaining a three-dimensional (3D) representation of one or more light sources inside a sample, such as a mammal. Mammalian tissue is a turbid medium, meaning that photons are both absorbed and scattered as they propagate through tissue. In the case where scattering is large compared with absorption, such as red to near-infrared light passing through tissue, the transport of light within the sample is described by diffusion theory. Using imaging data and computer-implemented photon diffusion models, embodiments of the present invention produce a 3D representation of the light sources inside a sample, such as a 3D location, size, and brightness of such light sources.
In one aspect, the present invention relates to a method for obtaining a three-dimensional representation of a light source distribution located inside a turbid sample. Surface light image data is provided from light emitted from a surface of the sample originating from the light source distribution located inside the sample. Light data internal to the sample surface is then obtained based on this provided surface light image data. In a specific embodiment, the surface light image data is converted into photon density just below the sample surface, and this photon density is then used to obtain the light data internal to the sample surface to thereby result in a three-dimensional representation of the light source distribution within the sample.
In yet another aspect, the present invention relates to an imaging system for obtaining a three-dimensional representation of a light source located inside a sample. The imaging system comprises an imaging chamber having a set of walls enclosing an interior cavity. The imaging chamber also includes a camera mount configured to position a camera and a moveable stage apparatus. The movable stage apparatus includes a transport mechanism and a stage configured to support the sample within the interior cavity. The stage is coupled with the transport mechanism for movement of the sample to one of a plurality of positions in the interior cavity. The imaging chamber further includes a light transport mechanism for transmitting light emitted from a surface of the sample. The imaging chamber also includes a processor designed or configured to provide surface light image data from light emitted from the surface of the sample originating from the light source distribution located inside the sample. The processor is further configured to obtain light data internal to the sample surface to obtain a three-dimensional representation of the light source distribution based on the surface light image data.
In still another aspect, the present invention relates to a computer program product. The computer program product comprises a computer readable medium and program instructions provided via the computer readable medium. The program instructions comprise reconstruction instructions for obtaining a three-dimensional representation of a light source located inside a sample. The reconstruction instructions are capable of performing one or more of the above described method operations.
These and other features of the present invention will be described in more detail below in the detailed description of the invention and in conjunction with the following figures.
The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
In the following detailed description of the present invention, numerous specific embodiments are set forth in order to provide a thorough understanding of the invention. However, as will be apparent to those skilled in the art, the present invention may be practiced without these specific details or by using alternate elements or processes. In other instances well known processes, components, and designs have not been described in detail so as not to unnecessarily obscure aspects of the present invention.
Imaging System
The 3D light reconstruction techniques of the present invention may be implemented within any suitable system. Several embodiments of imaging systems in which are suitable for implementing the techniques of the present invention are described further in U.S. patent application Ser. No. 09/905,668 filed by Nilson et al. on Jul. 13, 2001, now U.S. Pat. No. 7,113,217 issued Sep. 26, 2006, entitled MULTI-VIEW IMAGING APPARATUS. The entire disclosure of this application is incorporated herein by reference for all purposes.
The system 10 generally images and processes low intensity light sources using a light sensitive camera. Light from the light source refers to photons and electromagnetic energy anywhere in the visible to near-infrared (NIR) part of the spectrum in the wavelength range of 400-950 nm. It is understood that some intensities imaged and processed in system 10 are not readily detectable by human vision. For example, low intensity light emitted from a sample may have a surface radiance between about 103 to about 1010 photons/second/centimeter squared/steradian, where the lower end of this range is typically well below human detection levels.
In the illustrated embodiment, the imaging system 10 includes an imaging chamber 12 adapted to receive a light-emitting sample in which low intensity light, e.g., luciferase-based luminescence, is to be detected. A high sensitivity camera 20, such as an intensified or a charge-coupled device (CCD) camera, is coupled with the imaging chamber 12. The camera 20 is capable of capturing luminescent, photographic (i.e., reflection based images) and structured light images of the sample within imaging chamber 12. The camera 20 may optionally be cooled by a suitable source such as a refrigeration device 22 that cycles a cryogenic fluid through the camera via conduits 24.
An image processing unit 26 optionally interfaces between camera 20 and a computer 28 through cables 30 and 32, respectively. The computer 28, which may be of any suitable type, typically comprises a main unit 36 that contains hardware including a processor, memory components such as random-access memory (RAM) and read-only memory (ROM), and disk drive components (e.g., hard drive, CD, floppy drive, etc.). The computer 28 also includes a display 38 and input devices such as a keyboard 40 and mouse 42. The computer 28 is in communication with various components in the imaging chamber 12 via cable 34. Alternatively, a computer may be integrated with the imaging equipment in a single unit.
To provide control and communication for components in system 10, computer 28 may be implemented with any suitable combination of hardware and software for controlling and monitoring any of the devices in system 10. Components controlled by the computer 28 may include camera 20, the motors responsible for camera 20 focus, the camera lens, f-stop, one or more motors coupled to a moveable stage included in chamber 12, etc. Computer 28 also communicates with a display 38 for presenting imaging information to the user and also acts an interface to control the imaging system 10.
Computer 28 also includes suitable processing hardware and software for image processing and data manipulation as described herein. For example, computer 28 may be configured with software to build a 3D representation of a light source using light emission measurements from the surface of a sample. In addition, the computer 28 may be configured to produce 3D surface topography using 2D structured light images taken from one or more positions of the stage in the interior cavity. These 3D light construction techniques are further described below. Alternatively, the computer 28 may be integrated with the other components of the imaging system 10 to form a stand alone device.
In one implementation, the 3D light reconstruction techniques discussed further below require bioluminescent surface radiance and surface topography measurements over the entire sample surface. Thus, the imaging system also includes mechanisms for capturing images of the sample surface from a variety of views and positions. Preferably the imaging system meets the following goals. First, it is desirable for the camera to remain fixed, because the various cables and supply lines for cooling the camera are too cumbersome to move during imaging. Second, the sample preferably remains horizontal during imaging. Finally, the imaging system is preferably configured to obtain a 3D surface topography of the sample as input to the reconstruction techniques described further below. Any suitable combination of hardware and software may be used to implement these preferred goals.
As shown, a moveable stage apparatus is disposed in the interior cavity of chamber 12 (
In one implementation, light transport device 120 includes an angled mirror 121 that reflects light from the sample 106 on stage 204 through aperture 122. Outer wall 123 is substantially cylindrical and includes aperture 122 that enables light to pass from the sample 106 on stage 204 via mirror 121 to imaging lens 262 (
In the illustrated embodiment, light transport device 120 is rotatably coupled to chamber 12 and rotates about a fixed axis in direction 258. The moveable stage apparatus is capable of two degrees of freedom to position the stage 204 (and sample 106) at a plurality of positions relative to the light transport device 120 so as to capture light from different sides of the sample to thereby form multiple view images of the sample. The moveable stage apparatus allows an image of the sample, or portions thereof, to be captured by a camera from different views, angles, and positions within the imaging chamber without repositioning the posture of the sample relative to the stage 204.
The movable stage apparatus may be formed from any suitable number, type, and arrangement of components for achieving multiple positioning and viewing of the sample. Several embodiments of a multiple-view imaging systems are described in the above referenced patent application by Nilson et al., which embodiments are incorporated herein by reference. Preferably, the movable stage apparatus also includes sensor mechanisms for sensing a position of the sample to be used in subsequent data analysis procedures as described further below.
In one embodiment, a light source is provided within the barrel of mirror assembly 120 (not shown) to illuminate the sample or specimen in the imaging chamber 12. The light source may be continuously illuminated or flashed to capture photographic images of the sample and is turned off when capturing luminescence images.
A structured light illuminator is preferably integrated into the system for reconstructing a surface topography of the sample. In a general implementation, the imaging system preferably includes a mechanism for projecting a grid of lines onto the sample from an angle, e.g., from 20 to 30 degrees from normal. The grid of lines are displaced, or phase shifted relative to the platform, when they encounter an object with finite height. Using conventional equations for structured light analysis, the surface topography data for the sample over its entire surface can be determined from the phase shift of the lines. The line spacing may vary based on the sample surface texture and sample size, but line spacing in the range of 0.5 to 2 lines per mm may be suitable for a mouse sample. Closer line spacing provides higher resolution, but the lines are more difficult to track on rough surfaces such as fur. The surface topography data is used to build a 3D representation according to the techniques described below, e.g., to set boundary conditions for the 3D reconstruction.
In a specific embodiment, a simple Kohler projection scheme is used as the structured light source. In this case, the ruling may be illuminated by a diffuse LED source and the ruling is then projected onto the animal stage with a magnification of approximately 10�. An example of this system as incorporated in system 10 is shown in
Such an imaging system as described with respect to
3D Source Reconstruction
In many turbid samples such as a mammalian subject, light traveling from a light source inside the sample and emitted from the sample surface is scattered in the sample interior (e.g., the mammal tissue) such that light propagation through the sample is diffusive in nature (
Emission of light from a sample surface is generally specified in units of radiance, defined as photons/sec/cm2/steradian. The imaging system described herein is calibrated to report surface intensity in units of radiance. The surface radiance can be related to the photon density just inside the sample surface, using a model for photon propagation at the tissue-air interface. The photon density just inside the surface can then be related to the distribution of light emitting reporters inside the sample using a diffusion model. Thus, the present invention relates the surface radiance of a turbid sample measured with an imaging system to the distribution of light emission inside the sample. More specifically, the present invention produces a 3D representation of an internal light source using reconstruction techniques that utilize the light data emitted from the sample surface. The reconstruction techniques employ an input data set that consists of a) a topographical surface representation of the sample, and b) a set of measurements (e.g. surface images) of the light radiance over at least a portion of the surface. To facilitate processing, the surface representation may be divided into surface elements and the interior of the sample may be divided into volume elements or voxels that constitute a volume element mesh. The light source distribution within the sample is described by elements of the volume element mesh.
One useful application of the invention is to reconstruct one or more bioluminescent or fluorescent light sources, or a source distribution, inside a living animal subject, such as a mouse, using one or more images of the surface light emission. This finds use in oncology, infectious disease research, gene expression research, and toxicology, for example. The present invention is suitable for use with samples having a complex surface, such as an animal subject (e.g. a mouse). As the term is used herein, a complex surface is any surface that cannot be described solely using a single polygonal description. The reconstruction techniques described herein place no restrictions on the source distribution, such as the number of light sources in the sample or the sizes and shapes of the sources, and no restrictions on the geometry, size or shape of the surface.
Light data internal to the sample surface generally refers to mathematical representation or approximation of actual light within the sample interior. This may include a set of points or volume elements, each characterized by 3D position and a source strength. In one embodiment, the present invention divides the sample interior into volume elements where each volume element is considered to contain a point light source at its center. A solid mesh of these volume elements then defines a collection of point sources used to approximate the actual light source distribution within the sample. For example, a solid mesh of cubic volume elements is suitable.
The surface representation refers to the surface topography of the sample and is embodied by a mathematical description or approximation of the actual surface. The surface representation need not include the entire sample, and may include a portion of the sample relevant to a particular imaging scenario. With a mouse for example, the surface representation might not necessarily include the entire mouse such as distal portions of the tail and distal portions of every foot. Thus, the surface representation is meant to broadly refer to any surface portion of the sample and not necessarily the entire sample. Typically, the surface representation includes one or more surface elements or regions of interest on the sample that produce surface light emission data related to the internal light source. For user convenience, the surface representation is often displayed in a pictorial depiction such as a 3D depiction derived from structural light construction techniques.
The sample containing the light source comprises a turbid interior of some sort. A turbid interior in this case refers to a volume that does not allow unimpeded transport of light. The turbid interior may comprise one or more mediums, structures, solids, liquids, gases, etc. In one embodiment, the sample is modeled as homogeneous such that each representative volume element in the sample is characterized by identical light transport properties. In another embodiment, the sample is represented as heterogeneous such that various representative volume elements in the sample are characterized by different light transport properties. In a mammalian sample such as a mouse for example, the interior may comprise a mixture of tissues, bones, organs, etc., each of which may be characterized by separate light transport properties in a heterogeneous model.
The present invention presents several methods for reconstructing a three-dimensional light source distribution internal to a sample based on the surface light emission, as will be described in greater detail below. Briefly, a set of structured light and luminescent images are first acquired, e.g., obtained with a system as described above. The surface topography of the animal is reconstructed using structured light algorithms and a surface mesh is generated. Let the surface elements be enumerated with the integers j. Using one or more luminescent images, the orientation of the imaging system, and the orientation of the surface mesh, the photon density, ρj, just below the surface of the jth element can be determined. The photon density just below the surface is related to the light intensity emitted from the surface (Eq. 1) as will be detailed below. A set of volume elements can be constructed in the volume interior to the surface. Let the volume elements be enumerated with the integers i. The source strength in each volume element, Si, is linearly related to the photon density just below the surface through a Green's function kernel, Gij, yielding a set of linear equations (Eq. 4) as will be detailed below.
Process flow 500 uses 3D reconstruction techniques that manipulate light data emitted from a sample surface. The reconstruction techniques employ data that provides information about the geometry of the sample and the spatial distribution of the light emission from the sample surface. This may include data that comprises a) a surface representation of the sample, and b) a set of measurements (e.g. images) of the light emission over at least a portion of the surface. One format for this data comprises (1) a surface representation defining the surface of the sample, (2) a set of light emission images from the sample surface, and (3) a set of parameters that define the spatial relationship between the sample and each image.
Process flow 500 begins by obtaining input data (502 and 504) used in the 3D reconstruction techniques. For example, process flow 500 may begin by obtaining a surface representation (502). To facilitate processing, the surface representation may be divided into surface elements or a suitable surface mesh approximating the actual surface of the sample (502). For example, the surface mesh may be defined by a set of connected polygons, where each polygon is a surface element. The number of surface elements may vary according to the size of the sample and a desired solution accuracy. Also the density of surface elements may vary from point to point on the surface mesh. In general, the accuracy of a surface representation is improved by increasing the number of surface elements.
Process flow may also obtain surface light emission data from the sample (504). For imaging system 10, the surface light emission data is contained in images captured by camera 20. The images include a set of measurements of the light emission over one or more portions of the surface. In one embodiment, multiple images of the sample are obtained from multiple views of the sample relative to the camera. In this case, each image provides a different two-dimensional view of the surface light emission from the sample. Multiple images may be taken to provide additional data from multiple angles.
The image data may then be mapped back onto the surface of the sample. Since a camera produces 2D data, the image data is manipulated according to the geometry between the sample surface and the camera lens to derive values of the light emission intensity (or radiance) at the surface.
Process flow 500 then converts the surface light emission data into light data internal to the surface to obtain the three-dimensional representation (506). The surface emission intensity is related to the photon density just inside the sample surface. The present invention thus converts values of light emission intensity for each surface element into photon density just inside the surface. Referring again to
Here, c is the speed of light, n is the index of refraction of the sample medium, T is the transmission coefficient for light exiting the sample through the surface element, and θ is the internal emission angle, which is related to the external emission angle θ2 through Snell's law:
The parameter Reff is the average internal reflection coefficient calculated from the following formulae:
Thus, the internal reflectivity Reff depends on the index of refraction of the medium underneath a surface element. In tissue for example, Reff is typically in the range of 0.3-0.5.
Eqs. (1) and (2) may thus be used to convert surface emission data measured at each surface element to values of the photon density beneath the surface. As the term is used herein, the subscript j enumerates a set of surface elements. ρj is then the value of the photon density calculated at the jth surface element. Further description of the conversion between surface light emission data into light data internal to the surface to obtain the three-dimensional representation is provided in
A photographic image is then captured (524). In an alternative embodiment, a "live mode" is used during photographic imaging of the sample to observe the sample in real time. The live mode includes a sequence of photographic images taken frequently enough to simulate live video. Upon completion of photographic capture, the photographic image data is transferred to an image processing unit 26 and/or a processor in computer system 28. These may be used to manipulate and store the photographic image data as well as process the data for display on computer monitor 38.
In one embodiment, the present invention uses structured light during image capture. Thus, with stage 204 at a desired position, a structured light image may be captured (526). Structured light image capture may be accomplished using a structured light projection system as described above, and may also include preparation of the structured light projection system (525) and any other components of imaging system 10 used in the structured light image capture. Upon completion, the structured light image data is transferred to an image processing unit 26 and/or a processor in computer system 28, which may be useful in building a 3D representation of the sample.
Subsequently, with stage 204 at a desired position or at the same position as a previously taken photographic or structured light image, the imaging apparatus 10 is prepared for luminescence image capture (527). Such preparation may include selecting luminescent exposure time and binning level using the computer 28, and turning off the lights inside chamber 12. When ready, the CCD camera 20 then captures (514) the luminescence image over a set period of time (up to several minutes). The luminescence image data are transferred to the image processing unit and/or a processor in computer 28.
At this point, a user may manipulate and store the luminescence image data as well as process it for display on the computer display 38. The manipulation may also include overlaying the luminescent image with the photographic image and displaying the two images together as a 2-D "overlay" image, with the luminescence data typically shown in pseudocolor to show intensity. As mentioned, the photon emission data may represent the specific pixels on the camera 20 that detect photons over the duration of the image capture period. This overlay image may then be the basis for user analysis; and may be analyzed and manipulated as desired. In particular, an analysis may include a summation of the illumination magnitudes over the pixels within a portion of the luminescence representation. Note that although the discussion will focus on a single luminescence representation for the overlay image, the process flow 520 may include taking multiple luminescence representations from the same position of stage 204, e.g., at the same time or a later time (530).
Stage 204 may then be moved to a second position (531). While the stage is at the second position, one or more photographic, structured light, and/or luminescence images of the sample may be captured as described above. Image collection may further continue by capturing images of the sample from alternate positions and views of the sample. For 3D reconstruction, photographic, structured light, and/or luminescence images of the sample may be captured from a number of positions. For example, image capture may occur at anywhere from 2 to 200 positions of the sample within the imaging chamber. The preferred number of images is 8, spaced every 45 degrees. In one embodiment, this process is automated and controlled via computer 28.
After a suitable number of structured light images have been captured from various angles and stored, computer 28 may then process the structured light data from each angle to generate a structured light representation (532). Each structured light image provides the surface topography for approximately the facing half of the sample.
In another embodiment, process flow 520 and imaging apparatus 10 reconstruct the 3D surface topography of the sample using a sequence of images. By taking images from several viewing angles, e.g., about every 45 degrees, the entire 3D surface of the sample can be reconstructed by "stitching" together the partial surface reconstructions obtained from each view. A sequence of images may then be taken at different viewing angles and used in reconstructing the sample's 3D surface topography. The 3D surface topography and image data may also be used in reconstructing the 3D location, brightness, and size of the light source within the sample. Once the images are received by processor 28, a suitable reconstruction algorithm is applied to the data to obtain the 3D surface topography. As one of skill in the art will appreciate, there are numerous algorithms for reconstructing a surface from structured light images. For example, the phase shift of each line at all points on the image can be determined from a 2D Fourier transform. Such a process is described in detail in the article entitled "Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry," by M. Takeda, H. Ina and S. Kobayshi, JOSA 72, 156-160 (1982), which article is incorporated herein by reference in its entirety. The actual surface height is then computed by "unwrapping" the phase map. Such a process is described in detail in the textbook entitled "Two-Dimensional Phase Unwrapping, Theory, Algorithms, and Software" by D. C. Ghiglia and M. D. Pritt, (John Whiley and Sons, New York, N.Y., 1998), which textbook is incorporated herein by reference in its entirety. Together, a structured light photographic representation of the sample and a luminescence representation of the sample may be combined to form a structured light superposition or 3D overlay image, with the luminescence data typically shown in pseudocolor to visually characterize intensity.
Process flow 510 begins by imaging a structured light reference to produce a pattern without the sample (511 and
Subsequently when the sample is in the imaging chamber, the sample is imaged with structured light (512 and
Process flow 510 then proceeds by imaging the sample without structured light (513 and
The background data is then converted to a wrapped phase (514 and
Surface topography for the sample is then calculated (516 and
The above processes (511-516) may then be repeated (517) from different views and positions. Imaging a sample from multiple views provides additional information that helps techniques described herein provide a more accurate 3D surface rendering. The multiple images, or the partial surfaces obtained from each view in the 3D imaging system, are then registered together to form a complete 3D surface (518 and
Process flow 540 assumes possession of a surface representation for the sample and possession of light emission data from the sample. Process flow 540 begins by dividing the surface representation into surface elements (541). The number of surface elements will vary according to the sample surface area and the desired solution accuracy. The number of surface elements should be large enough to capture photon density details and variation across the surface. For example, between about 100 and about 10,000 surface elements may be suitable for a mouse.
In addition, process flow 540 divides the sample interior volume into volume elements (542). In one embodiment, each volume element is considered to contain a point light source at its center. A solid mesh of volume elements then defines a collection of point sources used to approximate the actual light source distribution. In some cases, the density of the solid mesh increases near the light source to provide increased information in this space, while density of the solid mesh decreases in areas where no activity of interest is taking place (no light generation or transport). In addition, as will be described below with respect to loop 556, the volume element size may vary during solution attainment according to various adaptive meshing techniques. For example, the initial volume element size may range from about 0.1 cm3 to about 1 cm3, and the final volume element size for volume elements close to the source may reduce from about 1*10−3 cm3 to about 1*10−2 cm3. In a specific example, the initial volume element size may be about 1 cm3, and the final volume element size for volume elements close to the source may reduce to about 8*10−3 cm3.
Process flow 540 then establishes a relationship between the surface elements and volume elements (544). In one embodiment, the reconstruction method uses a linear relationship between the source emission strength and the photon density at the surface. In a specific embodiment, the linear relationship is described by a Green's function. The Green's function contains all of the information about the transport of photons inside the sample, including the effects of inhomogeneities in the volume and internal reflection at the boundary. The Green's function describes the transport of photons inside the sample from each point in the source distribution to the inside of each surface element of the sample.
When the medium inside the sample is assumed or modeled as homogeneous, one useful form for the Green's function is a simplified approximation in which the surface of the sample is treated locally as a planar interface oriented perpendicular to a line connecting a volume element center and a surface element. The photon density at the surface is the analytical solution for a point source in a semi-infinite slab using the partial-current boundary condition. Since the solution is only a function of the distance between the volume element and the surface, the simplified Green's function can be calculated for all pairs of volume elements and surface vertices with minimal computational expense.
With a linear relationship between the source strength in each volume element and the photon density at each surface element described by a Green's function Gij, the photon density at the jth surface element may be approximated by the sum of the contributions from all the volume elements:
Light transport in turbid media such as tissue is dominated by scattering and is essentially diffusive in nature. The condition for diffusive transport is that the scattering coefficient μs be greater than the absorption coefficient μa so that the change in the photon density is small between scattering events. The photon density produced by a source power density, Ui, in a homogeneous medium may be represented by the diffusion equation:
In this case, the Green's function is the solution to Eq. (5) subject to the boundary condition imposed by the surface of the sample. For a sample modeled as homogeneous, a useful approximate solution for the Green's function uses a planar approximation at the surface boundary.
This simplified Green's function is the analytical solution for a point source in the semi-infinite slab using the partial-current boundary condition:
In the simplified model just described, the simplified Green's function depends only on the distance between the volume element and the surface. It is not necessary to use an analytical form such as the simplified approximation to define the Green's function.
The present invention does not rely on an analytical form such as the approximation described above. In another embodiment, a look-up table may define the Green's function. The look-up table may be created by previous measurements of photon transport in a sample (or similar sample approximated to be substantially equal to the current sample), or by computational simulations using techniques such as Monte Carlo or finite element modeling. This particular method is useful for samples consisting of inhomogeneous media, such as animal subjects. In this case, the optical properties, μa and μs from Eq. 8, now have spatial dependence.
The planar boundary approximations discussed above work best for smooth surfaces with a large radius of curvature, and for cases where the absorption coefficient is not too small (μa>0.1 cm−1). An advantage of the planar approximation technique described above is that it is computationally convenient for solving the diffusion equation with an arbitrary complex boundary such as a mouse. Areas with more structure, such as the head or the limbs of a mouse, may benefit from a more accurate model of the boundary. Using a finite element modeling code to calculate the Green's functions is one option to obtain a more accurate boundary model. Finite element codes such as Flex PDE, from PDE Solutions, Inc. may be used for example. Another option will be to extend the planar surface approximation to first order in curvature, which may allow continued use of analytic expressions for Gij.
Once the Green's function is determined, the reconstruction is obtained by solving the system of linear equations that relate the photon density at the surface to the source distribution inside the object. Process flow 540 then proceeds by solving for all the internal volume elements (546). More specifically, given the modeling described above, the reconstruction techniques solve the system of linear equations that relate the photon density at the surface to the source distribution inside the sample. Thus, once the Green's function is determined, it may be evaluated for every volume element-surface element pair, in order to obtain the system of linear equations (Eq. 4). The final step of the reconstruction method is to solve the linear system, Eq. (4), for the source strengths Si. Referring back to Eq. (4), since ρ is known, and Gij can be determined as described above, the reconstruction techniques then solve for Si. Typically, there is no exact solution to the linear system because the collection of point sources is only an approximation of the actual source distribution. One suitable reconstruction is then the best approximate solution of the linear system.
In one embodiment, the linear system is converted into an optimization problem to find an approximate solution. In this case, a cost function is used to define the optimization problem. One suitable cost function may be represented by the sum of the source strengths:
The cost function is subject to one or more linear constraints. A first suitable set of constraints is that the source strengths be positive definite:
A second suitable set of constraints is a system of linear inequalities based on the system of linear equations (4). It requires that the contributions to the photon density summed over all the volume elements be less than the measured value of the photon density at each surface element:
In a specific embodiment, an optimum solution for source strengths Si is found by maximizing the cost function (10) subject to constraints (11) and (12).
Process flow 540 then solves for the current optimal solution in the set of solutions (550). The optimization problem described above may be solved using linear analysis techniques. One particularly efficient technique is the SIMPLEX method.
The solution quality may be assessed (552). In one embodiment, the assessment measures the difference between the observed photon density and the calculated photon density. For example, a "chi squared" criteria may be used:
The value of χ2 measures the difference between the observed photon density ρi and the calculated photon density
Determination of internal 3D light source distribution data based on surface light emission data may be embedded in one or more iteration loops. Iteration may allow for refinement of the volume mesh and may allow searches for the optimal sampling of the surface elements and the optimal weighting function configuration. In general, the convergence of the reconstruction is improved by reducing the size of the linear system. In one embodiment, reconstruction techniques of the present invention iteratively vary one or more of: the volume element configuration, the surface element configuration, and/or the cost function configuration.
Iteration may also assist solution attainment. The SIMPLEX method converges rapidly to a solution, and hence has the advantage of being a computationally efficient algorithm. To assist the SIMPLEX algorithm in finding the global maximum, and hence the optimum solution, the SIMPLEX calculation may be repeated numerous times while systematically varying key elements in the algorithm (554). This can be achieved by using adaptive meshing, or adaptive gridding, to vary the number of volume elements, and by using a subset of the surface elements.
Loop 556 (
An additional iterative improvement may be obtained by varying the number of surface elements, NS, used in obtaining the three-dimensional representation (loop 555). Using a subset of the surface elements of the surface mesh reduces the number of constraints in the problem, which may simplify solution calculation. The number of surface elements may be used to sample the surface uniformly. In this case, process flow 540 iterates for different values of NS corresponding to sampling the surface element mesh at different densities, and use the quality assessment (552) to determine the best solution among the different values of NS. For example, if the number of surface elements is between about 100 and about 300 surface elements for a small mouse, an iteration step size between about 10 and 50 may also suitable.
Another iteration loop varies a cost function to improve solution obtainment. For example, the cost function may be modified to include a weighting factor Wi:
The weighting factor Wi is the contribution of the ith volume element to the photon density over the entire surface. The exponent γ adjusts the relative contribution to the cost function of the interior volume elements and those volume elements close to the surface. When γ=0, then the interior volume elements have relatively greater weight. When γ=1 the volume elements near the surface have greater weight. Process flow 540 may be iterated while varying γ to search for solutions where the source is both near and far from the surface. For example, the step size may be varied by about 0.01 to about 0.2 for a range of γ from 0 to 1. In a specific embodiment, the step size was varied by about 0.05 for a range of γ from 0 to 1. Once again, quality assessment (552) may be used to identify the best solution.
In a specific embodiment, the SIMPLEX calculation is imbedded in a search routine that consists of two optimization loops. The inner loop uses adaptive gridding to optimize the configuration of the volume mesh. The outer loop searches for the optimum values of the parameters NS and γ. Each step of the search algorithm is tested using the chi-squared criteria. The global solution is defined as the one that minimizes χ2.
Although process flows 500, 510, 520 and 540 have been described with many simplifications to expedite processing, the present invention is not limited by these simplified computational methods. For example, the Green's Function may be calculated without many of the simplifications described above, even at the cost of increased computational requirements. In addition, while process flows 500, 510, 520 and 540 describe a specific method of obtaining measurements of light emission from the sample based on the system illustrated in
Further, although the present invention has been described so far with respect to a bioluminescent source, the present invention may be used to obtain 3D reconstructions of any type of light sources, including one or more fluorescent sources. For a fluorescent source, the relationship between the surface elements and the volume elements may be altered (544). For example, a Green's function in the linear system may be multiplied by a second Green's function that describes the transport of the excitation light from the sample surface to the volume elements. In a specific approximation, the Green's function in the linear system (4) may be modified to be the product of two Green's functions:
The first Green's function, Gi E, describes the transport of excitation light from the excitation source at the surface of the sample to the ith volume element. The second Green's function, Gij F, describes the transport of the fluorescent light from the ith volume element to the jth surface element. Both Green's functions can be determined from analytical expressions, such as the simplified approximation described above in the case of a homogeneous medium, or from look-up tables in the case of an inhomogeneous medium. The excitation and fluorescent light are typically at different wavelengths, and thus the fluorescence does not stimulate additional fluorescence. The system of linear equations (4) is still valid, and process flow 540 can be used as outlined above to determine the fluorescent light source distribution.
The present invention is also well suited to handle noise in the input images. Any practical imaging system will have a limited dynamic range and be subject to noise sources. This may compromise the fidelity of the images used as input data in the reconstruction, and consequently may degrade the quality of the 3D representation. To this end, the present invention may also include techniques designed to improve its performance when the input images are noisy and/or have a limited dynamic range.
A limited dynamic range is particularly evident when imaging bioluminescence from sources imbedded in tissue, because the light emission intensity typically varies over many orders of magnitude across the sample surface. If the imaging camera imposes a limited dynamic range and a region of highest intensity is set to the camera's upper limit, then there will probably be regions in the image where the emission intensity falls below the bottom of the dynamic range. These regions of the image will be received as noise; and correspond to a 'noise floor'.
The reconstruction techniques provided herein map images of surface light emission onto the three-dimensional sample to determine the value of the photon density underneath the surface. With noise in the images, the reconstruction techniques map only those regions of the images that are above the noise floor. This can be done by defining a threshold for each image that is a fraction of the peak intensity. In one embodiment, the threshold is related to the peak intensity and dynamic range of the camera. In a specific embodiment, the threshold may be larger than the number represented by dividing the peak intensity by the dynamic range. For example, if the dynamic range of the camera is 1000 and the peak intensity in the image is IP, than a suitable value for the threshold may be IP/500. Only the regions of the image that are above the threshold are mapped onto the sample; and those regions below the threshold are not used. As a result, there will be regions of the sample surface that are empty after mapping is completed, that is, that have no photon density values associated with the surface mesh. Typically, these will tend to be the parts of the surface that are the farthest away from the bioluminescent source.
Process flow 540 solves the following optimization problem: maximize the total source strength subject to the constraint that the calculated photon density is less than the measured photon density everywhere on the surface. However, process flow 540 may also account for empty parts of the surface. This is because when the photon density is unknown, the constraints on the source strength are removed for those volume elements near the empty regions. Thus, there may be insufficient information to determine the source strength in those volume elements. The modification of process flow 540 consists of eliminating volume elements in the volume grid that are insufficiently constrained by the existing photon density information. This is achieved by comparing the contribution of a volume element to the photon density in the empty and non-empty surface regions. For example, if P and Q represent the sets of surface elements that consist of the empty and non-empty regions, respectively, then the criteria for removing the ith volume element from the volume grid is:
The constant κ may have a value in the range of 1-10. The criteria (16) is applied to each volume element during the formation of the initial volume grid (542) and at each iteration, if used.
In addition to having a limited dynamic range, realistic images may contain noise. One minimum noise contribution may be represented by the shot (Poisson) noise associated with the sampling of discrete numbers of photons in each image pixel. When shot noise dominates, the signal-to-noise ratio in the image varies with the square root of intensity. This suggests that the regions of highest intensity, or equivalently those regions of the surface having the highest photon density, should have the relatively smallest amount of noise. To account for this noise, the assessment for solution quality may altered (552). For example, expression (13) may be modified to account for noise. More specifically, each term in the sum may be weighted by a factor of the photon density ρi to become:
The reconstruction techniques of the present invention will typically be implemented by a suitable processor or computer-based apparatus. Referring to
Regardless of computer system 350 configuration, it may employ one or more memories or memory modules configured to store program instructions for obtaining a three-dimensional representation of a light source located inside a sample and other functions of the present invention described herein. Such memory or memories may also be configured to store data structures, imaging data, or other specific non-program information described herein.
Because such information and program instructions may be employed to implement the systems/methods described herein, the present invention relates to machine-readable media that include program instructions, state information, etc. for performing various operations described herein. Examples of machine-readable media include, but are not limited to, magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROM disks; magneto-optical media such as floptical disks; and hardware devices that are specially configured to store and perform program instructions, such as read-only memory devices (ROM) and random access memory (RAM). The invention may also be embodied in a carrier wave traveling over an appropriate medium such as airwaves, optical lines, electric lines, etc. Examples of program instructions include both machine code, such as produced by a compiler, and files containing higher level code that may be executed by the computer using an interpreter.
It should be borne in mind that although computer system 350 is discussed in some detail herein to facilitate discussion, the invention may be practiced using a variety of suitable computer-implemented techniques. In general, any suitable computer system may be employed for obtaining a three-dimensional representation of a light source located inside a sample. Further, the inventive reconstruction techniques disclosed herein may be implemented via a computer network, such as a local area network (LAN), wide area network (WAN) or a global computer network such as the Internet. In the latter cases, the reconstruction techniques may be implemented at least in part as downloadable computer software and data (e.g., applets such as JAVA™ applets from Sun Microsystems Inc.). The downloadable computer software and data may be kept on one or more servers on the network, accessible by any client computer or terminal capable and authorized for such access. Network computing techniques and implementations are well known in the art and are not discussed in great detail here for brevity's sake.
While this invention has been described in terms of several preferred embodiments, there are alterations, permutations, and equivalents which fall within the scope of this invention which have been omitted for brevity's sake. For example, images may be acquired and analyzed at one or more different wavelengths. It is therefore intended that the scope of the invention should be determined with reference to the appended claims.
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The operations and objectives of the Office of Research Services are guided by a number of strategic University documents, including:
Brock 2014: Knowledge, Engagement, Transformation, an academic plan outlining how Brock will move towards comprehensive status, intensifying its Research and Graduate Studies activities, but doing so without losing the student-centred focus on which the University has built its strong reputation.
Brock University Strategic Research Plan, which identifies areas in which Brock University's faculty members have created niches of excellence or that are viewed as strategic priorities for the advancement of research and scholarship at this university, in the Niagara Region and Ontario, and in Canada.
ORS also maintains an archive of research-related publications, including newsletters and information regarding research sponsorship.
Research Funding Reports
The University maintains statistics on sponsored research funding.


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Bristol Lightsaber Flashmob - Today's Christian Videos
Moving Video Featuring Misty Copeland, Steve Harvey, Steve Jobs Will Change Your Outlook On Life - @vids2inspire
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Embed vids2inspire 2850 views 2010-10-02T02:01:23 A flashmob converged in Bristol, England, to have the world's largest lightsaber fight. I wish I had been there!
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text: Moth to Flame is described as a "sheer neutral beige with violet pearl." It's a peachy beige with white shimmer and sparkle. On lips, it adds some warmth but primarily sparkle/shimmer. It wore well for three hours. The texture is slightly thick and fairly tacky. It's part of the permanent range. Chanel French Toffee (83) (LE, $27.00) is more shimmery. Chanel Zephyr (377) (LE, $29.50) is paler. Revlon Peach (P, $7.49) is more pigmented. MAC Sublime Shine (LE, $20.00) is similar. MAC Satin Slip (LE, $20.00) is more shimmery. Chanel Aurore (LE, $29.50) is similar. See comparison swatches.


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Outdoor Nautical Ceiling Fans
Outdoor nautical ceiling fans can make your outdoor space much more comfortable and relaxing. If you enjoy being outside, it may be time to consider investing in an outdoor ceiling fan. If you do a lot outdoor entertaining, a wet or damp rated ceiling fan will make your guests feel more comfortable by providing them with a constant cool breeze. Pair an outdoor nautical ceiling fan with some festive outdoor nautical lights and turn your outdoor space into a place people enjoy gathering.


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Find accommodations in Dublin with the hotel list provided below. Search for cheap and discounted hotel and motel rates in or near Dublin, TX for your corporate or personal leisure travel. We list the best Dublin Texas hotel rooms. Review the Dublin hotel list below to find the perfect lodging. We also have a map of the Dublin hotels. Planning a group? Lock in Dublin Group Hotel RatesThe Dublin center is approximately 11 miles from Lone Star Over Texas Indoor Rodeo Arena and 12 miles from Tarleton State University.
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Ohio Christian University Announces Candidate Forum
Ohio Christian University Chair of the Business & Government Department, Dr. David H. Garrison, announced that there would be a bipartisan Candidate Forum on October 9, 2012 at 6:30 P.M. The forum will be open to the public and will be held in the Maxwell Center at the university.
The Candidate Forum will include many local and state candidates from the Democrat, Republican, and independent parties including the offices of state senator, state representative, county commissioner, sheriff, county prosecutor, county treasurer, and clerk of courts. Additionally, representatives of U.S. Senate and U.S. Congress candidates have indicated they will attend.
The doors open at 6:00 P.M. for anyone who wants to visit with the various candidates and pickup materials. The forum will begin at 6:30 P.M.
The Candidate Forum was developed in conjunction with the new Government Relations major started at Ohio Christian University in order to give the students and the public an opportunity to be more informed about the various candidates' positions.
Each candidate will be given a short time to explain their views and reasons for running for office, after which, Dr. Garrison, a former U.S. Congressional candidate himself, will pose questions to each candidate specific for their office.