measurement of accurate attenuation of photon flux in tissue is important to obtain reconstructed images using single - photon emission computed tomography ( spect ) . computed tomography ( ct ) scanner provides attenuation correction data for spect as well as anatomic information for diagnostic purposes . x - ray beam used in ct scan is poly - energetic , therefore , we have used a copper filter to remove the low energy x - rays to obtain more accurate attenuation factor as described by kheruka et al . images obtained with and without filters were quantitatively evaluated by segmentation method to avoid human error . segmentation is a process of dividing an image into regions having similar properties such as gray level , color , texture , brightness , and contrast . image segmentation is an important tool for evaluation of medical images . in nuclear medicine , segmentation of images could play an important role to know the size and exact extent of the lesion . the techniques available for segmentation of images can be broadly classified into two categories . techniques based on gray levels , this can be further sub - classified as ( a ) amplitude segmentation methods based on histogram features , ( b ) edge based segmentation and ( c ) region based segmentationtechniques based on textural features . 
  techniques based on gray levels , this can be further sub - classified as ( a ) amplitude segmentation methods based on histogram features , ( b ) edge based segmentation and ( c ) region based segmentation techniques based on textural features . in medical image processing , segmentation based on gray level does not give the desired results whereas segmentation based on textural feature methods gives more reliable results . various methods available for textural feature extraction and classification based on the above approaches are : ( a ) co - occurrence matrix method based on statistical description of gray level of an image , ( b ) gray level run length method ( c ) fractal texture description method , ( d ) syntactic method , and ( e ) fourier filter method . further , as a comparison between the above - mentioned textures based approaches , spectral frequency - based methods are less efficient while statistical methods are particularly useful for random patterns / textures . whereas for complex patterns , syntactic or structural methods give better results . therefore , in this study the textural properties have been computed using first - order statistics or second - order statistics that are computed from spatial gray - level co - occurrence matrices ( glcms ) for evaluation of images . in medical image processing , segmentation based on gray level does not give the desired results whereas segmentation based on textural feature methods gives more reliable results . various methods available for textural feature extraction and classification based on the above approaches are : ( a ) co - occurrence matrix method based on statistical description of gray level of an image , ( b ) gray level run length method ( c ) fractal texture description method , ( d ) syntactic method , and ( e ) fourier filter method . further , as a comparison between the above - mentioned textures based approaches , spectral frequency - based methods are less efficient while statistical methods are particularly useful for random patterns / textures . whereas for complex patterns , syntactic or structural methods give better results . therefore , in this study the textural properties have been computed using first - order statistics or second - order statistics that are computed from spatial gray - level co - occurrence matrices ( glcms ) for evaluation of images . in this study , we have used aapm ct phantom and jaszczak spect phantom to obtain ct and spect images . axial images of ct phantom were acquired with 3 mm copper filter ( low intensity ) and without copper filter ( high intensity ) . all the images were acquired with hawkeye , ge healthcare spect / ct system using low - dose ct at 140 kvp , 2.5 ma and 400 mm field of view as shown in figure 1a and b. to generate correct air correction table in the presence or absence of filters , the daily x - ray calibration procedure has been repeated with and without 3.0 mm copper filter . in this process , the system takes full rotation without any object between the x - ray source and detector ( i.e. , in air ) and another full rotation with daily quality control phantom placed in between x - ray source and detector . computed tomography phantom cross - sectional images of resolution pattern . ( a ) without copper filter , ( b ) with copper filter for the validation of attenuation correction map of filtered ct images , jaszczak spect phantom was filled with 500 mbq of tc and spect study was acquired in 64  64 matrix size for all 60 views over 360 rotation . low dose ct images were acquired for attenuation correction to be used for reconstruction of spect images . two sets of axial spect images were reconstructed using attenuation map from both the ct images obtained without and with filter [ figure 2 ] . ordered subsets expectation maximization was used for reconstruction of spect images . axial computed tomography and single - photon emission computed tomography images of jaszczak single - photon emission computed tomography phantom acquired without and with a copper filter . ( a ) axial computed tomography image acquired without any additional filter , ( b ) reconstructed single - photon emission computed tomography image using the attenuation map from ( a ) , ( c ) axial computed tomography image acquired with additional 3 mm copper filter , ( d ) reconstructed single - photon emission computed tomography image using the attenuation map from ( c ) jaszczak spect phantom consisted of 6 solid spheres having diameter 9.5 mm , 12.7 mm , 15.9 mm , 19.1 mm , 25.4 mm , and 31.8 mm . to see the effect of filtration on the ct and spect images , the cross - sections of only large 3 solid spheres were analyzed quantitatively by segmentation method . segmentation method as described by sharma et al . was applied on the ct images ( without and with filter ) and spect images of jaszczak spect phantom obtained using without and with filter ct attenuation maps [ figure 3 ] . the textural properties have been derived using the first - order statistics and second - order statistics that were computed from spatial glcms . segmented computed tomography and single - photon emission computed tomography images of jaszczak single - photon emission computed tomography phantom . ( a ) segmented computed tomography image without filter , ( b ) segmented single - photon emission computed tomography image without filter , ( c ) segmented computed tomography image with filter , ( d ) segmented single - photon emission computed tomography image with filter further , the segmented images were analyzed quantitatively by measuring the diameters of the spheres in all set of the images , and the cross section areas of the spheres were calculated . quantitative measurement of quality is done based on a universal image quality index ( uiqi ) as proposed by wang and bovik . for quantitative analysis of image quality , we have used ct phantom , and images were acquired with 3 mm copper filter ( low intensity ) and without copper filter ( high intensity ) using low - dose ct ( 140 kvp and 2.5 ma ) . we have used q , the uiqi as proposed by wang and bovik to measure the image quality , this index measures image distortion as a combination of three factors : ( i ) loss of correlation , ( ii ) luminance distortion , and ( iii ) contrast distortion . the value of q is computed as follows : where x and y are mean values , x and y are standard deviations of original image x = { xi | i = 1 , 2 , n } and image acquired y= { yi | i = 1 , 2 , n } whose quality is to be measured , respectively and are computed as follows : the dynamic range of q is ( 1.0 to 1.0 ) , 1.0 is the best value which is achieved if yi = xi i.e. , the image quality of acquired image is same as that of the original image ( phantom image ) and 1.0 means a poor image quality and correlation . further , mean square error ( mse ) is also widely used as mathematical measure for measuring the image quality of images and is measured as follows : for quantitative analysis of image quality , we have used ct phantom , and images were acquired with 3 mm copper filter ( low intensity ) and without copper filter ( high intensity ) using low - dose ct ( 140 kvp and 2.5 ma ) . we have used q , the uiqi as proposed by wang and bovik to measure the image quality , this index measures image distortion as a combination of three factors : ( i ) loss of correlation , ( ii ) luminance distortion , and ( iii ) contrast distortion . the value of q is computed as follows : where x and y are mean values , x and y are standard deviations of original image x = { xi | i = 1 , 2 , n } and image acquired y= { yi | i = 1 , 2 , n } whose quality is to be measured , respectively and are computed as follows : the dynamic range of q is ( 1.0 to 1.0 ) , 1.0 is the best value which is achieved if yi = xi i.e. , the image quality of acquired image is same as that of the original image ( phantom image ) and 1.0 means a poor image quality and correlation . further , mean square error ( mse ) is also widely used as mathematical measure for measuring the image quality of images and is measured as follows : for quantitative analysis of image quality , we have used ct phantom , and images were acquired with 3 mm copper filter ( low intensity ) and without copper filter ( high intensity ) using low - dose ct ( 140 kvp and 2.5 ma ) . we have used q , the uiqi as proposed by wang and bovik to measure the image quality , this index measures image distortion as a combination of three factors : ( i ) loss of correlation , ( ii ) luminance distortion , and ( iii ) contrast distortion . the value of q is computed as follows : where x and y are mean values , x and y are standard deviations of original image x = { xi | i = 1 , 2 , n } and image acquired y= { yi | i = 1 , 2 , n } whose quality is to be measured , respectively and are computed as follows : the dynamic range of q is ( 1.0 to 1.0 ) , 1.0 is the best value which is achieved if yi = xi i.e. , the image quality of acquired image is same as that of the original image ( phantom image ) and 1.0 means a poor image quality and correlation . further , mean square error ( mse ) is also widely used as mathematical measure for measuring the image quality of images and is measured as follows : images obtained with 3 mm copper filters were having better resolution than the images obtained without a copper filter as shown in figure 1 . uiqi q was used to measure the quality of image acquired for ct phantom under different conditions , i.e. at the different hardness of x - ray beam and the results of same along with the value of q and mse as shown in table 1 . quality index of the images obtained with the filter was higher , and mse was low as compared to images obtained without a filter . quality index and mse at different hardness of the x - ray beam using ct phantom the segmented ct and spect images of jaszczak spect phantom showed good consistency in terms of a number of pixels and area of the circular cross - section of the spheres in filtered images whereas no correlation has been found in the segmented images without a filter . when we applied simulated annealing based fuzzy c - means segmentation on both the ct images with and without a copper filter , the ct images with filter showed remarkable improvement and all the six section of the spheres were clearly visualized . when we applied same segmentation method on the reconstructed spect images obtained without and with filter ct attenuation maps , the same observations were noted [ figure 3 ] . segmented spect phantom image reconstructed using without filter ct attenuation map showed only four circular cross - sections of the bigger spheres . whereas , with filter showed all the six cross - sections of the spheres very clearly . we have measured the diameter of the bigger three spheres for comparison and details are given in table 2 . as expected the mean intensity observed in the circular cross - sections of the spheres in the spect images reconstructed with filtered ct images were found quite low as no activity was contained inside the spheres . cold area ( low activity ) was very well visualized for three bigger spheres in spect images with filter whereas it could be seen only for one sphere in unfiltered image . measurement of diameter of bigger three spheres the original diameters of the largest three spheres were 31.8 mm , 25.4 mm , and 19.1 mm . the computed diameters on without filter ct and spect images are given in table 2 , which shows large variations of 17% , 13% , 2.6% , and 65.7% , 62.2% , 81.2 for ct and spect images respectively . on applying additional 3 mm copper filter , the measured diameter of the targets on ct and spect images became 29.4 mm , 24.8 mm , 20.1 mm , and 28.0 mm , 24.7 mm , 14.0 mm , respectively showing the variation of 7.5% , 2.4% , -5.2% , and 8.8% , 2.8% , 26.7% from the calculated values . this study shows that the estimations became more accurate on ct and spect images after applying additional 3 mm copper filter . moreover , the measurement of diameters of three big spheres on filter ct and spect images are in good agreement in contrast to large variations observed in that of without filtered images . the segmented ct and spect images of jaszczak spect phantom showed good consistency in terms of a number of pixels and area of the circular cross - section of the spheres in filtered images whereas no correlation has been found in the segmented images without a filter . when we applied simulated annealing based fuzzy c - means segmentation on both the ct images with and without a copper filter , the ct images with filter showed remarkable improvement and all the six section of the spheres were clearly visualized . when we applied same segmentation method on the reconstructed spect images obtained without and with filter ct attenuation maps , the same observations were noted [ figure 3 ] . segmented spect phantom image reconstructed using without filter ct attenuation map showed only four circular cross - sections of the bigger spheres . whereas , with filter showed all the six cross - sections of the spheres very clearly . we have measured the diameter of the bigger three spheres for comparison and details are given in table 2 . as expected the mean intensity observed in the circular cross - sections of the spheres in the spect images reconstructed with filtered ct images were found quite low as no activity was contained inside the spheres . cold area ( low activity ) was very well visualized for three bigger spheres in spect images with filter whereas it could be seen only for one sphere in unfiltered image . measurement of diameter of bigger three spheres the original diameters of the largest three spheres were 31.8 mm , 25.4 mm , and 19.1 mm . the computed diameters on without filter ct and spect images are given in table 2 , which shows large variations of 17% , 13% , 2.6% , and 65.7% , 62.2% , 81.2 for ct and spect images respectively . on applying additional 3 mm copper filter , the measured diameter of the targets on ct and spect images became 29.4 mm , 24.8 mm , 20.1 mm , and 28.0 mm , 24.7 mm , 14.0 mm , respectively showing the variation of 7.5% , 2.4% , -5.2% , and 8.8% , 2.8% , 26.7% from the calculated values . this study shows that the estimations became more accurate on ct and spect images after applying additional 3 mm copper filter . moreover , the measurement of diameters of three big spheres on filter ct and spect images are in good agreement in contrast to large variations observed in that of without filtered images . scatter - induced artifacts in the ct image can have a similar appearance in the emission images and can severely distort the attenuation - corrected images , making these images effectively useless as reported by nuyts et al . attenuation correction problem in spect and pet imaging has been studied by several authors , and various methods have been proposed to tackle this problem . the only option offered by all manufacturers of spect scanners is to incorporate x - ray ct - based attenuation correction algorithms in their systems , and it is bilinear and hybrid scaling methods . this method works well for clinical procedures when x - ray beam is monoenergetic . however , x - ray beam used in spect with low - dose ct is poly - energetic . there are other remaining challenges that can cause errors in the converted attenuation correction factors caused by contrast agents and respiratory motion as well as truncation and beam hardening . errors that are present in the ct - based attenuation image have the potential of introducing bias or artifacts in the attenuation corrected spect emission image as studied by kinahan et al . for pet / ct systems . uncorrected beam hardening and scatter build - up reduces measured attenuation along the lines of high attenuation . therefore , there is need to remove these low energy x - ray component , which we have achieved by using a copper filter . therefore , images obtained with 3.0 mm copper filter for attenuation correction are superior as it removes the low energies x - ray beam from the primary beam . the results obtained with segmentation were in agreement with the results obtained by kheruka et al . on the basis of this preliminary study and use of copper filter by kheruka et al . , we could conclude that use of 3 mm copper filter to harden the x - ray beam is optimal for removing the artifacts without causing any significant reduction in the photon flux of the resulting x - ray beam . we found that image quality has improved with almost no artifact ; a very common problem seen in inadequately filtered x - ray beams . it could be established that the images acquired with the filter are of good quality as compared to images acquired without 3.00 mm copper filter and are free from bloom artifact . this study also showed that segmentation of images is an important tool in analyzing the images which avoid the human error .
background : measurement of accurate attenuation of photon flux in tissue is important to obtain reconstructed images using single - photon emission computed tomography ( spect ) . computed tomography ( ct ) scanner provides attenuation correction data for spect as well as anatomic information for diagnostic purposes . 
 segmentation is a process of dividing an image into regions having similar properties such as gray level , color , texture , brightness , and contrast . 
 image segmentation is an important tool for evaluation of medical images . 
 x - ray beam used in ct scan is poly - energetic ; therefore , we have used a copper filter to remove the low energy x - rays for obtaining correct attenuation factor . 
 images obtained with and without filters were quantitatively evaluated by segmentation method to avoid human error.materials and methods : axial images of aapm ct phantom were acquired with 3 mm copper filter ( low intensity ) and without copper filter ( high intensity ) using low - dose ct ( 140 kvp and 2.5 ma ) of spect / ct system ( hawkeye , ge healthcare ) . for segmentation simulated annealing based fuzzy c - means , algorithm is applied . 
 quantitative measurement of quality is done based on universal image quality index . 
 further , for the validation of attenuation correction map of filtered ct images , jaszczak spect phantom was filled with 500 mbq of 99mtc and spect study was acquired . 
 low dose ct images were acquired for attenuation correction to be used for reconstruction of spect images . 
 another set of ct images were acquired after applying additional 3 mm copper filter . 
 two sets of axial spect images were reconstructed using attenuation map from both the ct images obtained without and with a filter.results and conclusions : when we applied simulated annealing based fuzzy c - means segmentation on both the ct images , the ct images with filter shows remarkable improvement and all the six section of the spheres in the jaszczak spect phantom were clearly visualized .