Title of Invention: Apparatus and method for registering virtual anatomy data Abstract: An image processing apparatus comprises a data receiving unit configured to receive medical imaging data and a registration unit configured to obtain a registration of the medical imaging data with model-based virtual anatomy data by determining a transformation between a coordinate space of the medical imaging data and a coordinate space of the virtual anatomy data based on the locations of anatomical landmarks in the medical imaging data and the locations of corresponding anatomical landmarks in the virtual anatomy data. Detailed Description: Part general_description_paragraphs: Part FIELD: Embodiments described herein relate generally to a method of, and apparatus for, registering medical imaging data with virtual anatomy data. Part BACKGROUND: It is well known to use medical imaging techniques to obtain imaging data that is representative of anatomical structures within the body of a patient or other subject. Volumetric imaging data may, for example, be obtained by the acquisition of a series of two-dimensional slices (usually axial), which may be combined to form a three-dimensional array of voxels. Volumetric imaging modalities may comprise, for example, computed tomography (CT), cone-beam computed tomography (CB-CT), magnetic resonance (MR) or ultrasound. In a CT data set, for example, each voxel usually has an associated intensity, measured in Hounsfield Units, which represents the attenuation of X-ray radiation by the respective, corresponding measurement volume. Medical imaging data may be specific to a particular patient, and to a particular scan of that patient. Medical imaging data can be in a variety of forms and can include any suitable data obtained from measurements by a medical imaging modality. Medical imaging data may be data that can be rendered, or otherwise processed, to obtain an image of at least part of a subject. A virtual anatomy provides a representation of the location of anatomical features and may, for example, comprise a synthetic, non-patient-specific representation of generic human anatomy in three dimensions. A virtual anatomy may provide features such as the identification of organs and other anatomical structures. Anatomical structures (for example, the liver or other organs) may be named in the virtual anatomy. Anatomical structures may be given a shape and a position within the body. Volumetric virtual anatomy data may comprise a set of voxels, for example a three-dimensional array of voxels, that may be similar to the three-dimensional array of voxels obtained through a medical imaging scan. For example, each voxel in the volumetric virtual anatomy data may have an associated intensity value. In volumetric virtual anatomy data, voxels may be assigned to anatomical structures within the human body, for example to provide a generic representation of the human body in which anatomical structures are segmented. It is known to map volumetric patient data comprising an array of voxels to volumetric virtual anatomy data comprising an array of voxels, for example using similar registration techniques to those that may be used to register one set of volumetric patient data to another set of volumetric patient data. One approach to mapping volumetric patient data to volumetric virtual anatomy data is to use image similarity-based registration techniques, for example optimization based on mutual information. Image-based registration techniques may be computationally intensive, and therefore may be slow. Other types of virtual anatomy data are known, in addition to volumetric virtual anatomy data comprising an array of voxels. For example, model-based virtual anatomy data is known in which anatomical structures are represented by models, for example surfaces or regions in three-dimensional space, rather than by labeled arrays of voxels. Part DETAILED DESCRIPTION: Certain embodiments provide an image processing apparatus, comprising a data receiving unit configured to receive medical imaging data and a registration unit configured to obtain a registration of the medical imaging data with model-based virtual anatomy data, wherein obtaining a registration of the medical imaging data and the virtual anatomy data comprises determining a transformation between a coordinate space of the medical imaging data and a coordinate space of the virtual anatomy data based on the locations of anatomical landmarks in the medical imaging data and the locations of corresponding anatomical landmarks in the virtual anatomy data. Certain embodiments provide an image processing method, comprising receiving medical imaging data and obtaining a registration of the medical imaging data with model-based virtual anatomy data, wherein obtaining a registration of the medical imaging data and the virtual anatomy data comprises determining a transformation between a coordinate space of the medical imaging data and a coordinate space of the virtual anatomy data based on the locations of anatomical landmarks in the medical imaging data and the locations of corresponding anatomical landmarks in the virtual anatomy data. An imaging data processing apparatus 10 according to an embodiment is illustrated schematically in FIG. 1. The image processing apparatus 10 comprises a computing apparatus 12, in this case a personal computer (PC) or workstation, that is connected to a CT scanner 14, a display screen 16 and an input device or devices 18, such as a computer keyboard and mouse. In the present embodiment, sets of imaging data are obtained by the CT scanner 14 and stored in memory store 20. In other embodiments, sets of imaging data may be loaded from a remote memory store. Computing apparatus 12 provides a processing resource for receiving, registering and displaying medical imaging data and virtual anatomy data. Computing apparatus 12 comprises a central processing unit (CPU) 22 that is operable to load and execute a variety of software modules or other software components that are configured to perform the method that is described below with reference to FIG. 2. The computing apparatus 12 includes a data receiving unit 24 for receiving medical imaging data, a landmark location unit 26 for locating landmarks within the medical imaging data, a registration unit 28 for registering the medical imaging data to a virtual anatomy, and a processing unit 30 for rendering and displaying images from the medical imaging data and/or virtual anatomy data. In the present embodiment, the data receiving unit 24, landmark location unit 26, registration unit 28 and processing unit 30 are each implemented in computing apparatus 12 by at least one computer program having computer-readable instructions that are executable by the CPU 22. However, in other embodiments, the various units may be implemented as one or more ASICs (application specific integrated circuits) or FPGAs (field programmable gate arrays), or as any other suitable combination of software and hardware. The computing apparatus 12 also includes a hard drive and other components of a PC including RAM, ROM, a data bus, an operating system including various device drivers, and hardware devices including a graphics card. Such components are not shown in FIG. 1 for clarity. The system of FIG. 1 is configured to perform a series of stages as illustrated in overview in the flow chart of FIG. 2. At stage 40 of FIG. 2, the data receiving unit 24 receives from memory store 20 a volumetric medical imaging data set 100 (indicated in FIG. 2 as patient imaging volume 100) obtained from a CT scan of a patient. The imaging data set 100 may comprise a series of DICOM (Digital Imaging and Communications in Medicine) files. In other embodiments, the data receiving unit 24 receives the imaging data set 100 from a remote data store, for example from a server which may form part of a Picture Archiving and Communication System (PACS). In further embodiments, the data receiving unit 24 receives the imaging data set 100 directly from the scanner 14. In the present embodiment, the imaging data set 100 was obtained from a CT scan taken using CT scanner 14, which is connected to image processing apparatus 10. In alternative embodiments, the CT scan is taken using any CT scanner. In other embodiments, the imaging data set 100 comprises data obtained from any radiological scanner that produces volumetric radiological data in any modality, for example CT, MRI, ultrasound, PET or SPECT. At stage 42, the landmark identification unit 26 uses a landmark location algorithm to automatically identify known anatomical landmarks in the imaging data set 100 and to determine the location of each anatomical landmark in the coordinate system of the imaging data set 100. An anatomical landmark is usually a well-defined point in an anatomy (in the present embodiment, the human anatomy). Anatomical landmarks may be defined anatomically, in relation to anatomical structure such as bones, vessels or organs. Examples of anatomical landmarks include the center of the right eye and the apex of the right lung. The anatomical definition of a landmark may be used to locate that landmark in many different medical imaging data sets, or in virtual anatomies. For example, if the center of the right eye is determined as an anatomical landmark, the landmark at the center of the right eye may be located in any medical imaging data set or virtual anatomy in which the center of the right eye is present, by any manual or automatic method that can locate that point in the anatomy. An anatomical landmark may be located in a data set and assigned a set of coordinates in the coordinate frame of that data set. The location of the anatomical landmark may be regarded as a point in coordinate space. It may be expected that the coordinate values for the anatomical landmark in one data set will differ from the coordinate values for the anatomical landmark in a different data set. For example, the coordinates of the anatomical landmark may differ due to differences in patient anatomy or patient positioning. In some embodiments, although a landmark may comprise coordinate data representing a location in a coordinate space of a volumetric data set comprising a set of voxels or other imaging data, the landmark may not itself include any of those voxels or imaging data. The anatomical definition of each anatomical landmark may be pre-determined by clinical experts, and each landmark has a clear identity. Different anatomical landmarks, and different numbers of anatomical landmarks, may be determined for different applications. Each anatomical landmark may be defined anatomically on a generic human body. The present embodiment uses a set of 127 known anatomical landmarks (anatomical landmarks for which anatomical definitions have been pre-determined). In other embodiments, a different set of anatomical landmarks may be used, which may comprise different landmarks (for example, the center of the right eye may be included as a landmark in one set of anatomical landmarks but not included as a landmark in another set of anatomical landmarks) or may comprise a different number of landmarks (for example, 100 rather than 127). In the present embodiment, for each of the set of 127 anatomical landmarks, the landmark location unit 26 determines whether that landmark is present in the imaging data set 100 by using a classification method to determine whether the relevant anatomy is present. For example, for the anatomical landmark defined at the center of the right eye, the landmark location unit determines whether the center of the right eye is present in the imaging data set 100 by using a trained classifier. If the relevant anatomy is not present, the landmark location unit 26 returns no coordinates for the anatomical landmark in the imaging data set 100. If the relevant anatomy is present, the landmark location unit 26 determines the location of the landmark in the imaging data set 100 as a set of coordinates in the coordinate space of the imaging data set 100. For example, the landmark location unit 26 determines the position of the center of the right eye as a point in the imaging data set, and returns the coordinates of that position. The determined location of the landmark is specific to the particular imaging data set 100. A similar process of detection and location is performed for each of the set of 127 known anatomical landmarks. Once the landmark location unit 26 has determined which of the 127 possible landmarks is present in the imaging data set 100, and has determined the location of each of the landmarks that is present, the landmark location unit 26 passes a list of landmark locations, each associated with a respective anatomical landmark, to the registration unit 28. In the present embodiment, the processing unit 26 detects the anatomical landmarks automatically using classifiers. Detection and localization of pre-defined anatomical landmarks in medical imaging data is performed by a classification forest which uses simple image features. Detection results may be refined with reference to the spatial relationships between the landmarks. In other embodiments, any other suitable method of landmark detection may be used. Methods of landmark detection may be as described in, for example, Mohammad A Dabbah, Sean Murphy, Hippolyte Pello, Romain Courbon, Erin Beveridge et al, ‘Detection and location of 127 anatomical landmarks in diverse CT datasets’, Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903415 (Mar. 21, 2014); doi:10.1117/12.2039157; http://dx.doi.org/10.1117/12.2039157; Criminisi, Shotton, Robertson and Konukoglu (2011), ‘Regression forests for efficient anatomy detection and localization in CT studies’, Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, 106-117; Donner, Menze, Bichof and Langs (2013), ‘Global localization of 3D anatomical structures by pre-filtered Hough forests and discrete optimization’, Medical Image Analysis, 17(8), 1304-1314, doi:10.1016/j.media.2013.02.004; or Liu and Zhou, ‘Anatomical landmark detection using nearest neighbor matching and submodular optimization’, Medical image computing and computer-assisted intervention (MICCAI), 7512, 393-401. FIG. 3 shows a medical image 60 which has been derived from an imaging data set 100 associated with a patient. The positions of three anatomical landmarks have been marked on the medical image 60: the inferior tip of the sternum 70, the superior aspect of the right iliac spine 71, and the superior aspect of the left iliac spine 72. At stage 44, the registration unit 28 receives a list of landmark locations 110 pertaining to a mesh-based virtual anatomy data set 120 from memory store 20, or from an alternative data store. In the present embodiment, the mesh-based virtual anatomy data set 120 is Zygote Body (see for example, Kelc R., Zygote Body: A New Interactive 3-Dimensional Didactical Tool for Teaching Anatomy. WebmedCentral ANATOMY 2012; 3(1):WMC002903) and the landmark locations within the mesh-based virtual anatomy data set have been pre-determined by an expert, who has manually identified and determined the position of each of the anatomical landmarks in the Zygote Body data set. In other embodiments, any other pre-existing or pre-determined model-based virtual anatomy data set may be used. Virtual anatomy data is available that does not comprise voxels. Virtual anatomy data that does not comprise an array of voxels may be referred to as model-based virtual anatomy data. Model-based virtual anatomy data may be virtual anatomy data that represents anatomical structures by defining surfaces or regions in three-dimensional space. Each anatomical structure in a model-based virtual anatomy may, for example, be represented by any appropriate representation of a region or surface such that the boundaries of the anatomical structure are defined in the virtual anatomy. For example, the representation may be a mesh, a function, a set of functions, or one or more virtual objects. One type of model-based virtual anatomy data that can be used may be mesh-based virtual anatomy data. In mesh-based virtual anatomy data, polygonal meshes may be used to represent anatomical structures. The model-based virtual anatomy data set may comprise virtual anatomy data in which the virtual anatomy is represented by three-dimensional surfaces or regions or models of such surfaces or regions. The model-based virtual anatomy data set may comprise mesh-based virtual anatomy data. The mesh-based virtual anatomy data set may comprise a plurality of surface meshes and/or a plurality of space-filling meshes. In some mesh-based virtual anatomies a set of surfaces are defined, each representing the surface of a respective anatomical structure in three dimensions. Each surface is represented by a polygonal mesh which comprises a set of points, the points linked by edges to form polygonal faces. The surfaces may be nested. For example, surfaces representing the surfaces of organs may be nested inside a surface that represents the surface of the skin. In some mesh-based virtual anatomies a set of three-dimensional objects are defined, each representing the three-dimensional shape and position of a respective anatomical structure. Each three-dimensional object is represented by a respective three-dimensional mesh. For example, in structural modeling (for example, finite element analysis) a space-filling mesh of polyhedra may be employed. A space-filling mesh of polyhedra may comprise a set of vertices in three dimensions, which are joined by edges to form a plurality of polyhedra. In some applications the polyhedra may typically be tetrahedra or cuboids. The spacings between the points in the set of points that form a space-filling mesh may be considerably greater than the voxel spacing would be in a volumetric virtual anatomy that represents the same anatomy. The model-based virtual anatomy data set may comprise a surface representation that is not mesh-based. Surfaces of anatomical structures may be defined using any appropriate surface representations. For example, the model-based virtual anatomy data set may comprise a surface representation that is based on control points. The surface representation may be based on splines, for example NURBS. Thus, each three-dimensional surface may be determined using splines, for example NURBS (non-uniform rational basis splines). In some virtual anatomies, a three-dimensional region may be defined for each anatomical structure using any appropriate method. For example, each region may be represented by a virtual solid object. Returning to the present embodiment, the mesh-based virtual anatomy data set 120 represents an entire human body. Therefore, each of the 127 landmarks that is anatomically defined may be identified and located on the virtual anatomy data set. In alternative embodiments, fewer landmarks are located in the virtual anatomy data set than are anatomically defined for the generic human body (for example, 127 landmarks are defined anatomically on the human body, of which 90 are located in the virtual anatomy data). In some such embodiments, the virtual anatomy data set 120 does not represent the entire body (for example, for particular applications the virtual anatomy data set 120 represents a part of the body, for example the head) and the set of landmark locations 110 includes only the locations of landmarks that are present in the virtual anatomy data set 120. In the present embodiment, the locations 110 of the anatomical landmarks on the virtual anatomy data set 120 are pre-determined manually by an expert before the start of the process of FIG. 2. Whilst in the present embodiment, the locations of landmarks in the virtual anatomy data set 120 are determined manually, in alternative embodiments, the locations of landmarks in the virtual anatomy data set 120 are determined automatically or semi-automatically using any appropriate landmark location method. In the present embodiment, it is not required that the determined location of each anatomical landmark in the mesh-based virtual anatomy data set 120 corresponds to a mesh vertex. The location of each anatomical landmark is only required to be a coordinate point in the coordinate system of the virtual anatomy data set 120, which may or may not correspond to a mesh vertex. In the present embodiment, the locations of the landmarks on the virtual anatomy data set 120 need only be determined once (in the present embodiment, before the process of FIG. 2 is started) and may then be used in numerous instances of the process of FIG. 2. However, in alternative embodiments, anatomical landmarks are identified and located in the virtual anatomy data set as part of stage 44. In some embodiments, the landmark locations 110 for the virtual anatomy data set are determined before, after, or at the same time as the location of landmarks in the medical imaging data set 100. Landmarks in the virtual anatomy data set 120 may be referred to as virtual landmarks. Each landmark location is a set of coordinates in the coordinate system of the virtual anatomy data set 120. The list of landmark locations 110 that is passed to the registration unit 28 may be referred to as a database of anatomical landmark locations in the virtual anatomy data set. FIG. 3 shows, along with the medical image 60 derived from the medical imaging data set 100, a virtual anatomy image 80 derived from a mesh-based virtual anatomy data set 120. In the present embodiment, the virtual anatomy image 80 is derived from Zygote Body. In other embodiments, any suitable mesh-based virtual anatomy data set may be used. The position of each of three landmarks has been marked on the virtual anatomy image 80: the inferior tip of the sternum 90, the superior aspect of the right iliac spine 91, and the superior aspect of the left iliac spine 92 (the same anatomical landmarks that are marked on the medical image 60). It may be seen that, prior to registration, anatomical landmarks in the virtual anatomy image 80 are in different positions from the positions of corresponding anatomical landmarks in the medical image 60. In the present embodiment, each of the set of landmark locations for the imaging data set 100 and the set of landmark locations 110 for the virtual anatomy data set 120 comprises all of the 127 defined anatomical landmarks. In other embodiments, the set of landmark locations for the imaging data set 100 comprises more or fewer landmarks than the set of landmark locations 110 for the virtual anatomy data set 120. The number of landmarks in the imaging data set 100 need not match the number of landmarks in the virtual anatomy data set 120. At stage 46, the registration unit 28 establishes a correspondence between the location of each landmark in the medical imaging data set 100 and the location of its corresponding landmark in the virtual anatomy data set 120. For example, as shown in FIG. 3, each of the medical imaging data set 100 and the virtual anatomy data set 120 includes the landmark at the inferior tip of the sternum (70 and 90 respectively). The registration unit 28 associates the location of the landmark at the inferior tip of the sternum 70 in the medical imaging data set 100 with the location of the landmark at the inferior tip of the sternum 90 in the virtual anatomy data set 120. It is to be expected that the location of each landmark will be different in the imaging data set coordinate space than in the virtual anatomy data set coordinate space, since each anatomical structure of the patient may differ from that of the virtual anatomy in size, shape and location, and the patient may be positioned differently in space from the virtual anatomy. At stage 48, the registration unit 28 receives the virtual anatomy data set 120 from the memory store 20. The virtual anatomy data set 120 comprises coordinates of each mesh vertex for each mesh in the virtual anatomy data set 120, and edges connecting the mesh vertices. Although in the present embodiment the registration unit 28 receives the virtual anatomy data set 120 after receiving the set of anatomical landmark locations 110 in the virtual anatomy data set, in other embodiments the virtual anatomy data set 120 and the determined set of anatomical landmark locations 110 in the virtual anatomy data set are received at the same time, or the virtual anatomy data set 120 is received before the set of anatomical landmark locations 110. At stage 50, the registration unit 28 performs a registration of the medical imaging data set 100 and the virtual anatomy data set 120 using the relationship between corresponding landmark locations that was determined at stage 46. In alternative embodiments, the registration unit 28 obtains a registration of the medical imaging data set 100 and the virtual anatomy data set 120 that has been performed by a different unit or on a different computing apparatus. The registration comprises a transformation between the coordinate space of the virtual anatomy data and the coordinate space of the medical imaging data. The location of each anatomical landmark that is present in the medical imaging data set 100 has a corresponding location for that anatomical landmark in the virtual anatomy data set 120. The aim of the registration process is to transform the medical imaging data set 100 into the coordinate system of the virtual anatomy data set 120 such that the location of each anatomical landmark in the transformed medical imaging data set coincides, as nearly as possible, with the location of the corresponding anatomical landmark in the virtual anatomy data set 120. While in the present embodiment the medical imaging data set 100 is transformed into the coordinate system of the virtual anatomy data set 120, in other embodiments the virtual anatomy data set 120 is transformed into the coordinate system of the medical imaging data set 100, or both data sets are transformed into the coordinate system of a further data set, for example a further medical imaging data set. The registration of the medical imaging data set 100 and the virtual anatomy data set 120 comprises determining a transformation from the coordinate system of the medical imaging data set 100 to the coordinate system of the virtual anatomy data set 120 and optimizing that transformation. The transformation is determined based on the locations of anatomical landmarks in the medical imaging data and the locations of corresponding anatomical landmarks in the virtual anatomy data. In the present embodiment, each landmark location is a set of coordinates, and only the landmark locations are used in the determining of the transformation. The information used to determine the transformation does not comprise, for example, intensity information associated with the anatomical landmarks. In the present embodiment, the transformation comprises an affine mapping of coordinates with 12 degrees of freedom on the medical image and virtual anatomy coordinate systems. In other embodiments, any other suitable transformation may be used. In the present embodiment, the transformation is calculated using a robust least squares regression. In other embodiments, any suitable method may be used. In the present embodiment, the transformation is a rigid transformation comprising rotation, translation and scaling. In other embodiments, the transformation is a non-rigid transformation comprising deformation, which may include local deformation. The registration unit 28 applies the optimized transformation to the medical imaging data set 100, thereby transforming each voxel of the medical imaging data set 100 into the coordinate system of the virtual anatomy data set 120 using a coordinate transformation comprising rotation, translation and/or scaling. In alternative embodiments in which the determined transformation is a non-rigid transformation, a non-rigid registration can be employed by calculating a warp field interpolated from the landmark coordinates. In other embodiments, registration unit 28 registers the virtual anatomy data set 120 and medical imaging data set 100 by determining a transformation from the coordinate system of the virtual anatomy data set 120 to the coordinate system of the medical image 100, and transforming the virtual anatomy data set in accordance with the determined transformation by transforming the coordinates of the mesh vertices in the virtual anatomy data set 120. At stage 52 of the process of FIG. 2, the processing unit 30 receives the virtual anatomy data set 120 and the transformed medical imaging data set (which has been transformed into the coordinate system of the virtual anatomy data set). In other embodiments, the processing unit 30 receives the virtual anatomy data set 120, the original medical imaging data set 100, and details of the registration between the virtual anatomy data set 120 and medical imaging data set 100. The processing unit 30 renders a combined image comprising a virtual anatomy image 80 derived from the virtual anatomy data set and a medical image 60 derived from the medical imaging data set 100, and displays the combined image on display screen 16. In the present embodiment, the combined image rendered by the processing unit 30 comprises an overlaid image in which the medical image 60 is overlaid on the virtual anatomy image 80 (the combined image is illustrated in FIG. 4). Since the medical imaging data set has been registered with the virtual anatomy data set, anatomical structures in the medical image 60 are displayed in a location that corresponds to their location in the virtual anatomy image 80. The processing unit 30 displays the overlaid image on display screen 16. In other embodiments, the processing unit 30 renders an overlaid image in which a virtual anatomy image 80 is overlaid on a medical image 60. In some embodiment, the combined image comprises one part of the body rendered as a virtual anatomy image 80, and another part of the body rendered as a medical image 60. For example, a heart or other organ from the virtual anatomy data set may be shown with lungs or another organ from the medical imaging data set. In some embodiments, the combined image comprises an overlapping image, a merged image, an inset image, a composite image or any other combination of images or imaging data. In some embodiments, a combined image is rendered by two-dimensional fusion rendering, in which the image value of each voxel in the combined image is a combination of the image value of that voxel in the virtual anatomy image 80 and the image value of that voxel in the medical image 60. In some embodiments a fusion slider is provided by which a user may alter the proportional contributions of the virtual anatomy image 80 and the medical image 60 to the combined image. In other embodiments, three-dimensional fusion rendering may be used, in which blending of the virtual anatomy with the medical image proceeds volumetrically. Three-dimensional rendering may be accomplished by ray-casting or other methods. In some embodiments, data derived from the medical imaging data set, such as a multi-planar reconstruction MPR), may be rendered as a combined image with the virtual anatomy data. One application of a display of a combined image such as that illustrated in FIG. 4 may be to show how the anatomical structures displayed in a medical image 60 relate to the rest of the human body. Although the anatomical structures (for example, the ribs) shown in FIG. 4 may be familiar to most lay people, some medical scans may cover smaller areas or appear more obscure to the lay viewer. In such cases, displaying the medical image 60 overlaid on an image of a representative human body may help the viewer (for example, the patient) to understand the context of their medical scan. In the present embodiment, the overlaid image comprising the medical image 60 overlaid on the virtual anatomy image 80 may be manipulated by a user. For example, the overlaid image is displayed in a medical image viewing application which allows the user to zoom in or out on the image or to rotate the image. If the user provides an input corresponding to an image manipulation (for example, the user rotates the image using a mouse action), the processing unit 30 renders a new overlaid image which still shows a medical image 60 overlaid on a virtual anatomy image 80, but with each image shown at a new viewing angle corresponding to the user's requested rotation. In alternative embodiments, at stage 52, instead of rendering a combined image the processing unit 30 renders a medical image 60 in a first frame and a virtual anatomy image 80 in a second frame. The medical image 60 and virtual anatomy image 80 are separate images in separate frames but are aligned with each other using the registration between the medical imaging data set 100 and the virtual anatomy data set 120. By displaying the medical image 60 and virtual anatomy image 80 in alignment, the images may be displayed such that an anatomical structure that is displayed at a first position in the first frame may be displayed at the same, or a corresponding, position in the second frame. The position of at least one anatomical structure in one of the first frame and the second frame may be dependent on the position of at least one corresponding anatomical structure in the other of the first frame and the second frame. For example, if the top of the head is at the top of the medical image 60 in the first frame, the top of the head may be at the top of the virtual anatomy image 80 in the second frame. Each frame may comprise a window, pane, screen region or display screen or any other display method by which separate images are displayed. The medical image 60 and virtual anatomy image 80 may be displayed adjacently or in proximity to each other, for example in a horizontal configuration (a side-by-side display) on a single screen, in a vertical configuration, on adjacent screens, or as part of a hanging protocol (in which a plurality of images is displayed, the order and relative positioning of the views being determined by the hanging protocol). Any display may be used that allows both images to be viewed. For example, the images may be displayed overlapping, or it may be possible to toggle between the two images by entering a user input. In some embodiments, the medical image 60 and virtual anatomy image 80 display at least one anatomical structure that is common to both images. In some embodiments, anatomical structures are displayed such the location and orientation of each anatomical structure is the same, or substantially the same, in the medical image 60 as it is in the virtual anatomy image 80. For example, each of the medical image 60 and the virtual anatomy image 80 may display a view of the patient's head, with the position of the head aligned between the two images (as a result of the registration between the medical imaging data set and virtual anatomy data set). In some embodiments, the horizontal and/or vertical position of an anatomical structure in the first frame may be the same, or substantially the same, as the horizontal and/or vertical position of a corresponding anatomical structure in the second frame. The corresponding anatomical structure in the second frame may be the same anatomical structure as is shown in the second frame (for example, the skull may be shown in both frames) or may be an adjacent or proximate anatomical structure (for example, the skull may be shown in the first frame and the eyes and other soft tissue in the second frame). In some embodiments, the position of an anatomical structure in the first frame may be offset from the position of a corresponding anatomical structure in the second frame, for example by a fixed offset value. The processing unit displays the medical image 60 and virtual anatomy image 80 on display screen 16. One example of a side-by-side display is illustrated in FIG. 5. Another example of a side-by-side display is shown in FIG. 6. Although side-by-side displays are referred to below with regard to the embodiments of FIG. 5 and FIG. 6, similar embodiments exist in which images are arranged vertically, placed on different screens, displayed overlapping, or displayed in any suitable relationship where both images can be viewed. By showing a medical image 60 adjacent or in proximity to a virtual anatomy image 80, a user may be able to compare the patient's anatomy as shown in the medical image 60 to a representative human anatomy as shown in the virtual anatomy image 80. This may assist a user in identifying anomalies in the patient's anatomy, or in describing such anomalies, for example to the patient. In some embodiments in which a medical image and a virtual anatomy are shown as separate images (and also in some embodiments in which a combined image is shown), performing an action on one of the medical image 60 and the virtual anatomy image 80 causes a corresponding action to be performed on the other of the medical image 60 and virtual anatomy image 80. For example, in some embodiments, the processing unit 30 receives a user input from user input device 18 which indicates an action to be performed on the medical image 60. The action to be performed may be any action that may be performed on a medical image, including but not limited to a manipulation such as a rotation, translation or scaling; a change in rendering such as a change of rendering preset, change of color settings, change of intensity or change of transparency; or a selection of a point or region of the image. The processing unit 30 performs the indicated action on the medical image 60, and also performs a corresponding action on the virtual anatomy image 80. In some embodiment, the corresponding action is an identical action. In other embodiment, the corresponding action is an equivalent action. For example, in one embodiment, the medical image 60 is rendered using a different color scheme from the virtual image 80. When the user requests a change in rendering color or intensity in the medical image 60, a different color or intensity may be applied to the virtual image 80, which is consistent with the relationship between the existing color schemes. For example, in one embodiment in which the medical image is displayed in grayscale and the virtual anatomy image is displayed in color, requesting lighter shades of grey in the grayscale image may result in different colors being used in the virtual anatomy image. In some embodiments, if the user requests a manipulation (for example, a rotation, translation or zoom) of the medical image 60, the same manipulation is performed on the virtual anatomy image 80. The user may thereby continue to directly compare the images when the images are manipulated. In some embodiments, selecting a point on the medical image 60 causes the corresponding point to be selected on the virtual anatomy image 80. For example, clicking on a point in the liver or on another organ in the medical image causes a corresponding point on the liver or other organ to be selected in the virtual anatomy image. The selected point is not required to be a landmark or to be part of an identified anatomical structure. Such selection may be used for the placing of measurements, the drawing of regions of interest, or other purposes. In one embodiment, selecting a point on the medical image 60 (for example, by clicking with a mouse) causes the medical image 60 to be displayed such that the selected point is in the center of the image, and simultaneously causes the virtual anatomy image 80 to be displayed such that the point on the virtual anatomy image that corresponds to the selected point on the medical image is in the center of the virtual anatomy image. Although the above embodiments are described with reference to an action performed on the medical image leading to a corresponding action in the virtual anatomy image, similar embodiments exist in which an action performed on the virtual anatomy image 80 leads to a corresponding action being performed on the medical image 60. In some embodiments, semantic information (which may be described as anatomical structure information) associated with the virtual anatomy data set 120 may be used to navigate the registered medical imaging data set. For example, in one embodiment, the location and extent of anatomical structures (for example, bones and organs) in the virtual data set is known, and such structures are labeled. Therefore, it is possible to navigate to particular anatomical structures in the virtual anatomy data set, for example by typing the name of an anatomical structure (e.g. ribs) into a text box. In one embodiment, typing, for example, ‘ribs’ or any other name of an anatomical feature into a text box associated with the virtual anatomy image 80 causes the virtual anatomy image 80 to be displayed such that the ribs (or specified anatomical feature) are displayed in the center of the virtual anatomy image 80 (the virtual anatomy image may be described as becoming centered on the ribs). For example, after ‘ribs’ is typed into the text box, the virtual anatomy image 80 changes to a zoomed-in virtual anatomy image showing the neighborhood of the ribs in the virtual anatomy. In the same embodiment, when the virtual anatomy image 80 becomes centered on the ribs in response to the text input, the medical image 60 also becomes centered on the ribs, the registration of the two data sets being used to provide equivalent views. Therefore the semantic knowledge (anatomical structure labeling) in the virtual anatomy data set may be used to navigate to a given structure in the medical imaging data set, using the registration between the data sets. In some embodiments, the medical image 60 and the virtual anatomy image 80 are rendered using corresponding rendering presets or other rendering settings. For example, the images may be rendered using the same rendering preset (set of rendering parameters) or equivalent rendering presets. In some such embodiments, the user may request a change of rendering settings (the user may give a rendering instruction) in one of the images. For example, the user requests a change of rendering settings in the virtual image 80. When the processing unit 30 then renders and displays a new virtual anatomy image 80 with the requested rendering settings, the processing unit 30 also selects rendering parameters for the rendering of the medical image 60 in dependence on the requested rendering parameters for the virtual anatomy image, and renders and displays a new medical image 60 using those rendering settings. Therefore, a rendering instruction applied to one image may be reflected in a corresponding rendering instruction being applied to the other image. In some embodiments, a rendering parameter that is requested for the medical image 60 results in a corresponding rendering parameter being used to render the virtual anatomy image 80. In some embodiments, a rendering parameter that is requested for the virtual anatomy image 80 results in a corresponding rendering parameter being used to render the medical image 60. The corresponding rendering settings may be the same as the requested rendering settings, or some or all of the rendering settings may differ from the requested rendering settings. For example, in some embodiments, a different rendering method is used to render a virtual anatomy image 80 from the mesh-based virtual anatomy data set 120 than is used to render a medical image 60 from the medical imaging data set 100. Therefore, when a change of rendering settings is requested for the virtual anatomy image 80, a different change in settings, or a change of different settings, may be required to produce the same visual effect in the medical image 80 as is produced in the virtual anatomy image 80. In the case where a common rendering preset is used for both images, changing the rendering preset for one of the images causes the rendering preset for the other image to be changed, so that the images continue to be displayed using a common preset. Using a common preset may allow the virtual anatomy image 80 and the medical image 60 to be directly comparable. In other embodiments, different rendering presets or other rendering settings may be applied to the medical image 60 and the virtual anatomy image 80. Using different presets may allow, for example, context to be displayed in the virtual anatomy image 80 that is not displayed in the medical image 60. For example, the medical image 60 may show only bones, while the virtual anatomy image 80 also displays organs. In some embodiments, a user may select a rendering preset or other rendering parameters for each of the medical image 60 and the virtual anatomy image 80, for example by using a drop-down menu. In some embodiments, the user may choose whether the rendering preset or other rendering parameter is applied to one of the images, or to both of the images. In the embodiment of FIG. 6, the user may select particular anatomical structures to be highlighted or otherwise emphasized in the virtual anatomy image 80. For example, in FIG. 6, the kidneys 82 are highlighted in the virtual anatomy image 80. In the embodiment of FIG. 6, it may not be possible to isolate a particular anatomical structure (such as the kidneys) for display in the medical image 60. In this case, anatomical structures are not segmented in the medical imaging data set 100 and therefore using a particular preset may return all anatomical structures with similar densities. However, it is possible to render the virtual anatomy image 80 with a highlighted anatomical structure, since the virtual anatomy data set 120 contains the surfaces of each of the anatomical structures, represented as a polygonal mesh. By highlighting anatomical structures in the virtual anatomy image 80, it may be easier to interpret or explain the same structures in the medical image 60. FIGS. 5 and 6 each show a single medical image 60 and a single virtual anatomy image 80. However, in other embodiments, several medical images 60 and several corresponding virtual anatomy images 80 may be displayed (for example, front, back and side views of each of the medical imaging data and the virtual anatomy data may be displayed simultaneously). In some embodiments, performing a manipulation or a change in rendering parameters on one image (for example, the frontal virtual anatomy image 80) causes the same manipulation or change of rendering parameters to be performed on a corresponding image (for example, the corresponding frontal medical image 60). In other embodiments, each image may be operated on independently. The embodiments of FIGS. 3, 4, 5 and 6 are each embodiments in which both a medical image 60 and a virtual anatomy image 80 are displayed at stage 52 (for example, as side-by-side images or as an overlaid image comprising the medical image 60 overlaid on the virtual anatomy image 80). However, in other embodiments, only one image (either a medical image 60 or a virtual anatomy image 80) may be displayed. In one embodiment, a medical imaging data set 100 and virtual anatomy data set 120 are registered using the method of steps 40 to 50 of the process of FIG. 2. The virtual anatomy data set 120 is transformed into the coordinate system of the medical imaging data set 100. At stage 52, the processing unit 30 renders a medical image 60 from the medical imaging data set 100. Although no image from the registered virtual anatomy data set 120 is displayed, the registered virtual anatomy data set 120 is used to add functionality to the medical imaging data set 100. For example, if a user clicks on a point in the medical image 60 (which may be referred to as a measurement point), the mapping to the virtual anatomy data set 80 can be used to determine a corresponding point in the virtual anatomy data set 80. In the virtual anatomy set, each anatomical structure (for example, each bone and organ) is identified. Therefore, when the user clicks on the measurement point in the medical image 60, the display returns to the user an estimate of which anatomical structure contains the clicked point. The virtual anatomy data set may therefore be used as an atlas (which may in this embodiment be described as a coarse atlas). Conversely, if the user requests a particular structure or location in the medical image 60, for example by typing ‘liver’ or the name of another organ into a text box, the definition of that structure or location in the virtual anatomy data set 120 may be mapped onto the medical imaging data set 100 in order to locate or navigate to that structure or location. For example, in one embodiment, when ‘liver’ is typed into the text box, the processing unit 30 determines the location of the liver in the virtual anatomy data set 120, uses that location and the registration of the virtual anatomy data set 120 and medical imaging data set 100 to determine an estimated location for the liver in the medical imaging data set 100, and places a labeled marker where the liver is estimated to be on the medical image 60. In another embodiment, when ‘liver’ is typed into the text box, the processing unit 30 renders and displays a medical image 60 which has been zoomed in to the area where the liver is estimated to be. Registration to the virtual anatomy data set may be used for study navigation. Study navigation may be provided without a virtual anatomy image being displayed. For example, in one embodiment, the user selects a desired organ from a menu. In other embodiment, the user types in a name. By using registration to the virtual anatomy, navigation of a medical image 60 may be provided even when that medical image 60 is derived from a medical imaging data set 100 in which no structures have been segmented. Although some navigation of the medical imaging data set 100 may be available by way of the landmark locations that have been determined for the medical imaging data set, navigation by such landmarks
{'bibliographic_information': "{'country': 'US', 'doc-number': '14555872', 'kind': 'B2', 'date': '20141128', 'invention_title': 'Apparatus and method for registering virtual anatomy data'}", 'source_file': './grant/2017/ipg170207.xml', 'source_data': 'USPTO-Grant'}