Title of Invention: IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, PROGRAM, AND SURGICAL NAVIGATION SYSTEM Abstract: Provided is an image processing device including: a matching unit that performs matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery; a shift amount estimation unit that estimates an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue; and a 3D model update unit that updates the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue. Detailed Description: CROSS REFERENCE TO RELATED APPLICATIONS This application is continuation application of U.S. patent application Ser. No. 16/314,461, filed on Dec. 31, 2018, which is a U.S. National Phase of International Patent Application No. PCT/JP2017/016163 filed on Apr. 24, 2017, which claims priority benefit of Japanese Patent Application No. JP 4179180424 filed in the Japan Patent Office on Jul. 12, 2016. Each of the above-referenced applications is hereby incorporated herein by reference in its entirety. TECHNICAL FIELD The present disclosure relates to an image processing device, an image processing method, a program, and a surgical navigation system. BACKGROUND ART A surgical navigation system that supports a surgeon by presenting a positional relationship between an operating site of a patient and a treatment tool at the time of surgery to a surgeon has been developed. For example, in the technique described in Patent Literature 1, a 3D model of the biological tissue is generated based on tomography images of a biological tissue including the operating site of the patient acquired before surgery. Then, at the time of surgery, three-dimensional positions of the biological tissue and the treatment tool are detected and a navigation image in which a display indicating the position of the treatment tool is added to the 3D model is caused to be displayed, for example, on a display device set in a surgery room. According to the technology, since the surgeon can perform surgery while ascertaining a distance between the operating site and the treatment tool, a distance between a part in which contact with the treatment tool in the biological tissue needs to be avoided and the treatment tool, and the like using the navigation image, smoother surgery can be executed and it is possible to improve the convenience of a surgeon. CITATION LIST Patent Literature Patent Literature 1: JP 2013-202313A DISCLOSURE OF INVENTION Technical Problem However, the actual position and shape of the biological tissue of a patient at the time of surgery may change from those before surgery due to changes in the position of the patient or influence and the like of treatment such as a laparotomy or craniotomy according to the surgery. In other words, the position and shape of the biological tissue of the patient at the time of surgery does not necessarily coincide with a 3D model generated based on information acquired before surgery. In such a case, according to the technology described in Patent Literature 1, the accurate position and shape of the biological tissue in conformity with a current state are not reflected in the navigation image, and the positional relationship between the biological tissue and the treatment tool is not accurately displayed. Therefore, appropriate navigation cannot be performed, and the convenience of a surgeon may be degraded. In view of this, the present disclosure proposes a novel and improved image processing device, image processing method, program and surgical navigation system which can further improve the convenience of a user. Solution to Problem According to the present disclosure, there is provided an image processing device including: a matching unit that performs matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery; a shift amount estimation unit that estimates an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue; and a 3D model update unit that updates the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue. In addition, according to the present disclosure, there is provided an image processing method including: performing, by a processor, matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery; estimating an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue; and updating the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue. In addition, according to the present disclosure, there is provided a program that causes a computer to execute an image processing method including: performing matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery; estimating an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue; and updating the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue. In addition, according to the present disclosure, there is provided a surgical navigation system including: a microscope unit that photographs a biological tissue including an operating site of a patient during surgery, and acquires a captured image with depth information; a position sensor that detects three-dimensional positions of the microscope unit, the patient, and a treatment tool; a display device that displays a navigation image in which a display indicating a position of the treatment tool is added to a 3D model of the biological tissue; and an image processing device that causes the display device to display the navigation image. The image processing device includes a matching unit that performs matching processing between a predetermined pattern on a surface of the 3D model generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery, a shift amount estimation unit that estimates an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery by the microscope unit on the surface of the biological tissue, a 3D model update unit that updates the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue, and a display control unit that causes the display device to display the navigation image using the updated 3D model. Information regarding a three-dimensional position of the photographing region is acquired on the basis of a result of detection by the position sensor and depth information of a captured image by the microscope unit. According to the present disclosure, in regard to a 3D model of a biological tissue including an operating site generated on the basis of information acquired before surgery and a captured image at the time of actual surgery, matching processing between an image representing a pattern on a surface of the 3D model and an image representing a pattern on a surface of the biological tissue included in the captured image is performed. Then, an amount of deformation from a state of the biological tissue before the surgery is estimated on the basis of a result of the matching processing, and the 3D model is updated on the basis of a result of the estimation. As a result, the updated 3D model reflects the actual position and shape of the biological tissue at the time of surgery, and thus if a navigation image is generated using the updated 3D model, a more accurate navigation image conforming to an actual situation can be obtained. Therefore, it is possible to further improve the convenience of a user who performs surgery using the navigation system. Advantageous Effects of Invention According to the present disclosure, convenience of a user can be further improved. Note that the effects described above are not necessarily limitative. With or in the place of the above effects, there may be achieved any one of the effects described in this specification or other effects that may be learned from this specification. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a block diagram which shows an example of a configuration of a surgical navigation system according to the present embodiment. FIG. 2 is a diagram for describing a function of a position sensor. FIG. 3 is a diagram which shows an example of a preoperative blood vessel pattern image. FIG. 4 is a diagram which shows an example of an intraoperative blood vessel pattern image. FIG. 5 is a diagram which shows an example of a calculation model of FEM. FIG. 6 is a diagram for describing swelling of a brain. FIG. 7 is a diagram for describing subsidence of a brain. FIG. 8 is a diagram which schematically shows a state of a human skull base. FIG. 9 is a diagram for describing, in a case in which subsidence of a brain occurs, a case in which a fixed point is set in consideration of a relationship between the brain and the spinal cord. FIG. 10 is a diagram which schematically shows an example of a general existing navigation image in a brain surgical operation. FIG. 11 is a diagram which schematically shows an example of a navigation image according to the present embodiment in a brain surgical operation. FIG. 12 is a flowchart which shows an example of a processing procedure of an image processing method according to the present embodiment. FIG. 13 is a diagram which shows a configuration of the surgical navigation system according to the present embodiment, including a detailed configuration of an observation device. FIG. 14 is a diagram which shows a state of surgery using the surgical navigation system shown in FIGS. 1 and 13. MODE(S) FOR CARRYING OUT THE INVENTION Hereinafter, (a) preferred embodiment(s) of the present disclosure will be described in detail with reference to the appended drawings. In this specification and the appended drawings, structural elements that have substantially the same function and structure are denoted with the same reference numerals, and repeated explanation of these structural elements is omitted. Note that the description will be made in the following order. 1. Background of the present disclosure 2. Configuration of surgical navigation system 3. Image processing method 4. Configuration example of observation device 5. Application example 6. Supplement Here, as an example, an embodiment in which a technology according to the present disclosure is applied to a brain surgical operation will be described in the following description. However, the present disclosure is not limited to such an example. The technology according to the present disclosure may also be applied to other types of surgery. In addition, a user who uses a surgery support system to be described below is described as a surgeon for the sake of convenience in the following description. However, this description does not limit the user using the surgery support system, and a subject using the surgery support system may also be another medical staff member such as an assistant or a nurse. 1. Background of the Present Disclosure Before describing preferred embodiments of the present disclosure, the inventors will describe the background of the present disclosure to make the present disclosure clearer. In a brain surgical operation, surgery is performed while observing an operating site of a patient in an enlarged manner through a microscope unit. For such a brain surgical operation, a surgical navigation system as described in Patent Literature 1 described above has been developed. In the surgical navigation system, a diagnostic image of a patient's brain is photographed by using computed tomography (CT) or magnetic resonance imaging (MRI) before surgery. Then, a 3D model of the brain is generated on the basis of the photographed diagnostic image. At the time of surgery, three-dimensional positions of a microscope unit, a patient, and a treatment tool are detected by a position sensor, and a navigation image in which a display indicating a region corresponding to a current field of view of the microscope unit or a display indicating a position of the current treatment tool is added to the 3D model is displayed on a display device installed in a surgery room on the basis of a result of the detection. According to such a surgical navigation system, since a positional relationship between the operating site (for example, a lesion to be resected) and the treatment tool can be displayed in real time in the navigation image, a surgeon can perform surgery while ascertaining the positional relationship. For example, the operating site may be hardly distinguishable in appearance from other normal tissues in some cases. In such a case, by reflecting the position of the operating site obtained by a prior examination of the 3D model, the surgeon can ascertain the positional relationship between the operating site and the treatment tool, which is difficult to discern with the naked eye, on the navigation image, and thus it is very useful. In addition, since positions of blood vessels inside the brain can also be reflected in the 3D model, positional relationships between the blood vessels and the treatment tool can be displayed on the navigation image. Therefore, for example, when the surgeon incises the brain and causes the operating site to be exposed, a risk of accidentally damaging the blood vessels can be reduced by referring to the navigation image. However, it is known that a phenomenon known as brain shift in which the brain, the shape of which is normally maintained by the cranial bone or cerebrospinal fluid, loses support in a craniotomy and the shape thereof changes occurs in a brain surgical operation. When brain shift occurs, a 3D model generated on the basis of information obtained before surgery differs from the shape of brain at the time of actual surgery, and thus a 3D model that accurately reflects the brain is not displayed in the navigation image. Therefore, the positional relationship between the operating site and the treatment tool and the positional relationship between the blood vessels and the treatment tool as described above cannot be accurately represented in the navigation image, which makes it difficult to perform appropriate navigation. Therefore, as one countermeasure against brain shift, CT photography or MRI photography is performed during surgery (so-called intraoperative CT photography or intraoperative MRI photography), and a technology for updating a 3D model displayed in a navigation image on the basis of the obtained diagnostic image has been proposed. According to this method, the 3D model reflecting the shape of the brain after brain shift is displayed in the navigation image, and it is possible to perform navigation conforming to the actual situation. However, in order to perform the intraoperative CT photography or the intraoperative MRI photography, it is necessary to install a dedicated CT device or MRI device in the surgery room or to arrange the surgery room and a CT room or an MRI room side by side, and thus cost for introduction is high. In addition, in order to perform the intraoperative CT photography or the intraoperative MRI photography, it is necessary to suspend surgery and perform the photography processing, and thus there are concerns that work is complicated, time for surgery increases, and a burden patient increases. Therefore, the inventors have conducted intensive studies on a technology capable of further improving the convenience of a surgeon by obtaining an appropriate navigation image more easily in a surgical operation, particularly in a brain surgical operation. The present disclosure was conceived as a result of this. Hereinafter, preferred embodiments of the present disclosure that the inventors have conceived of will be described. 2. Configuration of Surgical Navigation System With reference to FIG. 1, a configuration according to a preferred embodiment of the present disclosure will be described. FIG. 1 is a block diagram which shows an example of a configuration of a surgical navigation system according to the present embodiment. With reference to FIG. 1, a surgical navigation system 10 according to the present embodiment includes a microscope unit 110, a display device 120, a position sensor 130, and an image processing device 140. (Microscope Unit) The microscope unit 110 is a means for observing an operating site in an enlarged manner. The microscope unit 110 is configured with an image sensor, an optical system for guiding light from an observation target (observation light) to the image sensor, and the like accommodated in a housing. The image sensor generates a signal corresponding to the observation light, i.e., an image signal corresponding to an observation image, by receiving and photoelectrically converting the observation light. As described, the microscope unit 110 is an electronic imaging microscope unit that electronically photographs images. In addition, the microscope unit 110 is configured to photograph an image including depth information. For example, the microscope unit 110 has an auto focus (AF) function, and the microscope unit 110 can acquire depth information of a position which is in focus within an angle of view on the basis of information regarding a focal distance. In the brain surgical operation, a part of the cranial bone of a patient is craniotomized, and the surface of the brain exposed from the open head is photographed by the microscope unit 110. The microscope unit 110 transmits an image signal according to an acquired captured image, that is, information regarding the captured image, to the image processing device 140 (specifically, the matching unit 142, the brain shift amount estimation unit 143, and the display control unit 145 of the image processing device 140 to be described below). Note that the microscope unit 110 obtains depth information regarding the basis of a focal distance, but the present embodiment is not limited to such an example. The microscope unit 110 may be capable of photographing a captured image to which the depth information is added, and a configuration thereof may be arbitrary. For example, a distance measurement sensor may also be provided in the microscope unit 110. As the distance measurement sensor, for example, various types of sensors such as time-of-flight type sensors or laser scan type sensors may be used. According to the method, it is possible to measure a three-dimensional position of brain surface blood vessels more accurately than in the case of using a focal distance. Alternatively, the microscope unit 110 may be configured as a stereo camera, and depth information may also be obtained on the basis of disparity information. However, since a configuration of the microscope unit 110 becomes complicated in a case in which a distance measurement sensor or a stereo camera is used, the method of using a focal distance is preferable to more easily obtain depth information. In addition, in the present embodiment, the microscope unit 110 can be supported by an arm unit. In addition, an actuator is provided in each joint unit of the arm unit, an attitude of the arm unit is controlled by the actuator being driven, and the position and attitude of the microscope unit 110 can be controlled. A specific configuration of a support arm device (observation device) that supports the microscope unit 110 will be described in the following description (4. Configuration example of observation device). (Display Device) The display device 120 is installed at a position at which it is visible to a surgeon in a surgery room. A captured image of an operating site photographed by the microscope unit 110 is displayed on the display device 120 by control from the image processing device 140. The surgeon performs various types of treatments on an operating site while observing the operating site according to a captured image displayed on the display device 120. Moreover, a navigation image in which a display indicating a position of a current treatment tool is added to a 3D model of the brain is displayed in the display device 120 under a control of the image processing device 140. A surgeon performs surgery while ascertaining a positional relationship between the brain and the treatment tool (specifically, a positional relationship between a blood vessel and the treatment tool, a positional relationship between an operating site and the treatment tool, and the like) according to the navigation image displayed on the display device 120. Note that the details of a navigation image will be described below with reference to FIGS. 10 and 11. A specific configuration of the display device 120 is not limited, and as the display device 120, various known display devices, for example, a liquid crystal display device, an electro-luminescence (EL) display device, or the like, may be applied. Note that, although only one block showing the display device 120 is illustrated in FIG. 1 for the sake of convenience, a plurality of display devices 120 may also be provided in the surgical navigation system 10. In a case in which the plurality of display devices 120 are used, a captured image and a navigation image of an operating site can be displayed on separate display devices 120. Alternatively, in a case in which only one display device 120 is used, a display screen of the display device 120 is divided into two areas, and an operating site image and a navigation image can be displayed separately in these areas. (Position Sensor) The position sensor 130 detects three-dimensional positions of a patient's head, the microscope unit 110, and a treatment tool. FIG. 2 is a diagram for describing a function of the position sensor 130. FIG. 2 schematically shows a positional relationship among a patient 201, the microscope unit 110, a treatment tool 205, and the position sensor 130. As shown in FIG. 2, markers 203 and 207 are attached to the microscope unit 110 and the treatment tool 205. In addition, a marker 211 is also attached to the head of the patient 201 via a support member 209. The position sensor 130 is configured as a stereo camera, and can detect three-dimensional positions of markers 203, 207 and 211, that is, the three-dimensional positions of the head of the patient 201, the microscope unit 110, and a three-dimensional position of the treatment tool 205, on the basis of a captured image thereof. The position sensor 130 transmits information regarding the detected three-dimensional positions of the head of the patient 201, the microscope unit 110, and the treatment tool 205 to the image processing device 140 (specifically, a matching unit 142, a brain shift amount estimation unit 143, and a display control unit 145 of the image processing device 140 to be described below). Note that a configuration of the position sensor 130 is not limited to such an example, and various types of known sensors capable of detecting a three-dimensional position of an object may be used as the position sensor 130. For example, the markers 203, 207, and 211 may be magnets, and a magnetic sensor may be used as the position sensor 130. (Image Processing Device) The image processing device 140 performs various types of display control in the surgical navigation system 10. Hereinafter, functional units of the image processing device 140 will be described in detail. The image processing device 140 includes a 3D model generation unit 141, a matching unit 142, a brain shift amount estimation unit 143, a 3D model update unit 144, and a display control unit 145 as the functional units thereof. Note that the image processing device 140 can be, for example, a processor such as a central processing unit (CPU), a graphics processing unit (GPU), or the like, a control board on which memory elements such as processors and memories are mixed, a general information processing device such as a personal computer (PC), or the like, on which a processor is mounted. When a processor included in the image processing device 140 executes an arithmetic operation process in accordance with a predetermined program, each of the above-described functions can be realized. In the surgical navigation system 10, diagnostic images of a patient's brain are photographed before surgery, and information regarding these diagnostic images is managed to be accessed by the image processing device 140. The 3D model generation unit 141 generates a 3D model of the brain on the basis of the diagnostic images acquired before surgery. As a diagnostic image for generating a 3D model, any image used at the time of diagnosis may be generally applied. However, as will be described below, a 3D model of the brain generated by the 3D model generation unit 141 is used for the navigation image. Therefore, it is preferable that the diagnostic image be an image in which an operating site is clearly represented (that is, a disease emphasis image) such that a position of the operating site can be indicated on the 3D model. In addition, as will be described below, in the 3D model of the brain generated by the 3D model generation unit 141, an image representing a pattern of blood vessels (a blood vessel pattern image) is extracted from the 3D model, and used in matching processing of blood vessel pattern images. Therefore, it is preferable that the diagnostic image be an image in which the shape of the blood vessels is clearly represented (that is, a blood vessel emphasis image). In the present embodiment, one or a plurality of diagnostic images can be used in the generation of a 3D model in consideration of these points. For example, as the diagnostic image, an image photographed by MRI, magnetic resonance angiography (MRA), 3D-CT angiography (CD-CTA), 3D-digital subtraction angiography (3D-DSA), single photon emission CT (SPECT), and the like can be used. The 3D model generation unit 141 generates a 3D model by converting tomography images for each composition obtained by each method such as MRI into a 3D model using, for example, a technology such as volume rendering (VR) or surface rendering (SR) following a continuity of each composition. The processing of generating a 3D model using the 3D model generation unit 141 may be performed using various types of known methods, and thus the detailed description thereof will be omitted. The 3D model generation unit 141 provides information regarding a generated 3D model of the brain to the matching unit 142 and the 3D model update unit 144. The matching unit 142 calculates a three-dimensional position on the surface of the brain during surgery by matching feature points of an image representing a blood vessel pattern of the brain surface included in a 3D model of the brain generated by the 3D model generation unit 141 (hereinafter referred to as a preoperative blood vessel pattern image), and an image representing a blood vessel pattern of the brain surface photographed by the microscope unit 110 during surgery (hereinafter referred to as an intraoperative blood vessel pattern image). Specifically, the matching unit 142 first specifies a photographing direction of the microscope unit 110 and a craniotomy position on the basis of information regarding the three-dimensional positions of the head of the patient 201 and the microscope unit 110, which is provided from the position sensor 130. Next, the matching unit 142 extracts brain surface blood vessels from the 3D model of the brain generated by the 3D model generation unit 141, and generates a two-dimensional image in which the brain surface blood vessel is projected in the photographing direction of the microscope unit 110 at the specified craniotomy position, thereby generating a preoperative blood vessel pattern image. FIG. 3 is a diagram which shows an example of the preoperative blood vessel pattern image. As described above, this preoperative blood vessel pattern image can be clearly generated by using a blood vessel emphasis image as a diagnostic image for generating the 3D model of the brain. Next, the matching unit 142, on the basis of information regarding a captured image provided from the microscope unit 110, extracts an image representing brain surface blood vessels in the open head, that is, an intraoperative blood vessel pattern image, from the captured image. FIG. 4 is a diagram which shows an example of the intraoperative blood vessel pattern image. Then, the matching unit 142 performs matching processing between feature points of the generated preoperative blood vessel pattern image and intraoperative blood vessel pattern image. In the matching processing of feature points, for example, various types of known methods such as FAST, FASTX, STAR, SIFT, SURF, ORB, BRISK, MSER, GFTT, HARRIS, Dense, Simple Blob, and SmartAR (registered trademark) can be used. In these methods, it is possible to automatically obtain feature points (for example, as shown in FIGS. 3 and 4, a branch point X of blood vessels 213 and 215, a bending point Y of a blood vessel, and the like), and to evaluate a degree of matching between the two according to a degree of coincidence. At this time, since it is expected that there is blurring in distance and angle between the preoperative blood vessel pattern image and the intraoperative blood vessel pattern image due to brain shift, an affine transformation is performed on the preoperative blood vessel pattern image in a range with a minute magnification and a small angle to obtain a case in which a degree of coincidence is the highest in the changed range. As a result, brain surface blood vessels of a region (a photographing region) on the surface of brain exposed from the open head at the time of actual surgery and photographed by the microscope unit 110 are correlated with parts of the brain surface blood vessels of the 3D model generated by the 3D model generation unit 141. That is, a region on the surface of brain corresponding to the photographing region at the time of actual surgery is specified on the surface of the 3D model of the brain generated by the 3D model generation unit 141. Here, since a reflection of light has a thin stripe shape in a case in which an elongated convex-shaped object is photographed like a blood vessel, in a blood vessel pattern image photographed by the microscope unit 110, a center of one blood vessel is not displayed, and the blood vessel may be recognized in a shape of being broken into two lines. In this case, synthesis processing in which these are regarded as one blood vessel can be generally performed by the image processing in processes of the various types of known matching processing. However, since the blood vessel has a curved complicated shape, and the reflection direction of the light is not uniform, the recognized stripe-shaped portion does not necessary take such a form as to border the blood vessel, and blood vessels which should originally have been connected may be recognized to be interrupted due to the synthesis processing described above. Therefore, in this case, a blood vessel pattern image in which border of the blood vessel is, so-called, in a dotted line shape can be obtained as the intraoperative blood vessel pattern image. In such a case, the matching unit 142 determines matching between an intraoperative blood vessel pattern image in a dotted line shape and a preoperative blood vessel pattern image in a solid line based on a vector direction and a disposition pattern of each image. The matching unit 142 provides information regarding a matching result (that is, information regarding the specified region corresponding to the photographing region at the time of actual surgery on the surface of the 3D model of brain) to the brain shift amount estimation unit 143. Note that, in the above description, as the intraoperative blood vessel pattern image, an image extracted from a captured image by the microscope unit 110, that is, an image with visible light, is used, but the present embodiment is not limited to such an example. As the intraoperative blood vessel pattern image, for example, an image photographed with an emphasis on blood vessels of indocyanine green (ICG) fluorescence blood angiography or the like. In this case, the microscope unit 110 includes a function of performing fluorescence photographing and ICG fluorescence images of blood vessels can be acquired by the microscope unit 110. It is possible to make a feature point in the intraoperative blood vessel pattern image clearer, and to cause accuracy of the matching processing to be improved by using such an image photographed with an emphasis on blood vessels. The brain shift amount estimation unit 143 estimates an amount of deformation of brain caused by craniotomy from a preoperative state on the basis of a result of the matching processing by the matching unit 142. In the present embodiment, the brain shift amount estimation unit 143 estimates the amount of deformation of brain using a finite element method (FEM). Specifically, the brain shift amount estimation unit 143, first, generates a calculation model of the FEM by defining a three-dimensional mesh at each vertex of voxel of the 3D model of brain generated by the 3D model generation unit 141. FIG. 5 is a diagram which shows an example of a calculation model of the FEM. In the example shown in FIG. 5, a calculation model 217 of the FEM is generated by setting a mesh 219 in a regular tetrahedral shape with respect to the 3D model of brain. Next, the brain shift amount estimation unit 143 sets an initial condition and a boundary condition for the FEM calculation. First, initial condition will be described. Specifically, the brain shift amount estimation unit 143 sets an amount of displacement of brain in the open head before surgery on the basis of a result of the matching processing by the matching unit 142 as the initial condition. In the processing of setting the amount of displacement, the brain shift amount estimation unit 143 calculates three-dimensional coordinates in accordance with a current body position of the patient 201 in a region corresponding to a photographing region on the surface of the 3D model of brain in a case in which it is assumed that brain is not deformed are calculated on the basis of a result of the matching processing and information regarding a three-dimensional position of the head of the patient 201 provided from the position sensor 130. The three-dimensional coordinates are, that is, three-dimensional coordinates of each mesh of the region corresponding to the photographing region on a surface of the calculation model 217 in a case in which it is assumed that brain is not deformed. On the other hand, the brain shift amount estimation unit 143 calculates actual three-dimensional coordinates of the surface of the brain in the photographing region on the basis of information regarding the three-dimensional positions of the head of the patient 201 and the microscope unit 110, which is provided from the position sensor 130, and depth information included in information regarding a captured image provided from the microscope unit 110. A difference of these three-dimensional coordinates is the amount of displacement of brain in the photographing region, that is, the amount of displacement of brain in the open head. Since the brain shift amount estimation unit 143 obtains the amount of displacement of brain in the open head by calculating the difference, and sets a state in which a mesh of a position corresponding to the open head of the calculation model 217 is moved by the amount of displacement as the initial condition of the FEM calculation. Here, it is generally known that there are two types of brain shift at the time of craniotomy. They are brain swelling which can occur in an early stage of craniotomy and brain subsidence which can occur after an elapse of 10 minutes or more since the craniotomy. FIG. 6 is a diagram for describing brain swelling. FIG. 7 is a diagram for describing brain subsidence. FIGS. 6 and 7 schematically show a cross-section of the brain 221 at the middle. In a case in which swelling occurs as shown in FIG. 6, the brain shift amount estimation unit 143 expresses a displacement of a mesh positioned at an open head 223 among meshes positioned on the surface of the calculation model 217 by extending a distance between respective points in these meshes. On the other hand, in a case in which subsidence occurs as shown in FIG. 7, the brain shift amount estimation unit 143 expresses a displacement of the mesh positioned at the open head 223 among the meshes positioned on the surface of the calculation model 217 by reducing a distance between respective points in these meshes. Next, a boundary condition will be described. The brain shift amount estimation unit 143 sets a mesh which is in contact with cranial bone, dura, or the like and cannot physically move from an anatomical point of view as a fixed point with respect to the calculation model 217 as a boundary condition. A specific content of the boundary condition differs depending on an aspect (swelling or subsidence) of brain shift described above. In a case in which swelling occurs as shown in FIG. 6, a region other than the open head 223 in the brain 221 is fixed by the cranial bone and the dura, and it is considered that a displacement due to the swelling converges on the open head 223. Therefore, in this case, the brain shift amount estimation unit 143 sets a mesh positioned in a region other than the open head 223 among the meshes positioned on the surface of the calculation model 217 as a fixed point which is not deformed as the boundary condition. In FIG. 6, a region corresponding to a mesh treated as a fixed point on the surface of the brain 221 is indicated by a bold line in a simulative manner. On the other hand, in a case in which subsidence occurs as shown in FIG. 7, it is considered that a region below a contact point between an outer peripheral surface of the brain 221 and a vertical plane (shown by a dotted line in FIG. 7 in a simulative manner) showing a vertical direction which is a direction in which gravity acts is fixed by the cranial bone, and a region above it is displaced. Therefore, in this case, the brain shift amount estimation unit 143 sets a mesh positioned below the contact with the vertical plane among the meshes positioned on the surface of the calculation model 217 as a fixed point which is not deformed. In FIG. 7, in the same manner as in FIG. 6, a region corresponding to a mesh treated as a fixed point on the surface of the brain 221 is indicated as a bold line in a simulative manner. Alternatively, in a case in which subsidence occurs, another fixed point may also be set in consideration of a relationship between the brain 221 and a surrounding biological tissue (for example, spinal cords, blood vessel, nerves, and the like). Specifically, as shown in FIG. 8, large or small holes through which spinal cords, nerves, blood vessels, and the like pass are present in a human skull base. FIG. 8 is a diagram which schematically shows a state of the human skull base. FIG. 8 schematically shows a state in which a cranial cavity of human is horizontally cut and the human skull base is viewed from the above. A top of the page corresponds to the front. As shown in FIG. 8, for example, a large occipital hole 227 through which spinal cords pass, a burst hole 229 through which carotid arteries pass, and the like are present in a skull base 225. Since these spinal cords and carotid arteries are joined to surrounding brain tissues by connective tissues, a part of the brain 221 which is joined to spinal cords and the like can be regarded as a fixed point which is not deformed. Accordingly, the brain shift amount estimation unit 143 may also set, in addition to the mesh positioned below the contact with the vertical plane, a mesh positioned at a place which is opposed to a hole through which spinal cords or the like are inserted and is assumed to be joined to the spinal cords and the like among meshes constituting the calculation model 217, and a mesh positioned between these meshes as fixed points which are not deformed. FIG. 9 is a diagram for explaining a case in which a fixed point is set even in consideration of a relation between the brain 221 and the spinal cords, and the like in the case in which subsidence of the brain 221 occurs. FIG. 9 schematically shows a cross section of the brain 221 taken along midline similarly to FIGS. 6 and 7. In addition, in FIG. 9, similarly to FIGS. 6 and 7, a region corresponding to the meshes treated as fixed points on the surface of the brain 221 are indicated by a bold line in a simulative manner. In the example shown in FIG. 9, similarly to the case shown in FIG. 7, a mesh positioned below a contact point between the outer peripheral surface of the brain 221 and a vertical plane (shown by a dotted line in FIG. 9 in a simulative manner) is treated as a fixed point which does not deform. In the shown example, furthermore, a fixed point 231 which is a point fixed by being connected with a spinal cord, and the like on the surface of the brain 221 is added in consideration of a shape of the skull base 225 as described above. Then, a mesh positioned between the fixed point 231 and the contact point between the outer peripheral surface of the brain 221 and the vertical plane on the surface of the brain 221 is treated as a fixed point. In this manner, it is possible to set a boundary condition more suitable for an actual situation by setting a fixed point from an anatomical point of view in consideration of a shape of the cranial bone. After setting the initial condition and the boundary condition, the brain shift amount estimation unit 143 calculates an amount of deformation of the entire calculation model 217, that is, an amount of brain shift, by an FEM. In such an FEM calculation, for example, brain 221 is treated as an elastic body and the amount of deformation of the calculation model 217 is calculated under the initial condition and boundary condition described above by using a stress-strain relational expression for an elastic body. For a ratio of Young's modulus to Poisson, physical property values of the brain 221 obtained from various types of literatures, and the like may be used. Since the FEM calculation can be performed by various known methods, a description of specific processing in the FEM calculation will be omitted. Here, the brain shift amount estimation unit 143 calculates an amount of three-dimensional movement of a brain surface blood vessel in the open head 223 on the basis of a result of the matching processing by the matching unit 142 and the information regarding three-dimensional positions of the head of the patient 201 and the microscope unit 110 which are provided from the position sensor 130. Then, a shape of the deformed calculation model 217 is obtained such that a difference between the calculated amount of three-dimensional movement of a brain surface blood vessel in the calculated open head 223 and an amount of movement of a mesh positioned at the open head 223 is a minimum in the FEM calculation. The amount of displacement of each mesh 219 of the calculation model 217 in this state is the amount of movement of each voxel of the 3D model of the brain 221, that is, the amount of brain shift of the brain 221. The brain shift amount estimation unit 143 provides information regarding the obtained amount of brain shift, that is, the amount of movement of each voxel of the 3D model of the brain 221, to the 3D model update unit 144. The 3D model update unit 144 updates the 3D model of the brain 221 generated by the 3D model generation unit 141 on the basis of the information regarding the amount of brain shift obtained by the brain shift amount estimation unit 143. More specifically, the 3D model update unit 144 causes the 3D model to be deformed by moving each voxel of the 3D model of the brain 221 by an amount corresponding to the amount of brain shift obtained by the brain shift amount estimation unit 143. As a result, a 3D model which reflects the brain shift and in which an actual state of the brain 221 of the current patient 201 is more accurately represented is generated. The 3D model update unit 144 provides information regarding the updated 3D model of the brain 221 to the display control unit 145. The display control unit 145 controls driving of the display device 120 and causes the display device 120 to display a captured image of an operating site by the microscope unit 110. In addition, the display control unit 145 controls the driving of the display device 120, and causes the display device 120 to display a navigation image in which a display indicating a position of the treatment tool 205 is added to the 3D model of the brain 221 updated by the 3D model update unit 144. Note that, as described above, the captured image and the navigation image may be displayed on the same display device 120 or may be displayed on different display devices 120, respectively. Here, “the display indicating the position of the treatment tool 205” may be an icon indicating the treatment tool 205 or a real image of the treatment tool 205 photographed by the microscope unit 110. The navigation image may be obtained by combining an icon indicating the treatment tool 205 with the 3D model of the brain 221, or superimposing a real image of the treatment tool 205 on the 3D model of the brain 221. In addition, in the navigation image, a lesion which is the operating site may be displayed in an emphasized manner, or a blood vessel or the like which is a dangerous part to avoid a contact with the treatment tool may be displayed in the emphasized manner. The emphasis display is performed, for example, by superimposing and displaying annotation information (including symbols, words, and/or images) in an operating site or a dangerous part. For example, the annotation information is given in advance to the 3D model of the brain 221 generated before surgery, and in this emphasis display, the annotation information reflects the amount of brain shift obtained by the brain shift amount estimation unit 143, and is given to a corresponding part of the 3D model of the brain 221 which is updated by the 3D model update unit 144. As a specific display mode of a navigation image, various modes used for a navigation image in a general surgical navigation system can be applied. Here, FIG. 10 is a diagram schematically showing an example of a general existing navigation image in a brain surgical operation. FIG. 11 is a diagram schematically showing an example of a navigation image according to the present embodiment in a brain surgical operation. In FIGS. 10 and 11, a photographic image photographed by the microscope unit is shown by on the left side, and the navigation image is shown on the right side. As shown in FIG. 10, in the existing navigation image, since the 3D model of the brain 221 generated on the basis of a diagnostic image acquired before surgery
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