Abstract: A method includes obtaining an image of a subject to process via statistical testing. The method further includes obtaining a subject personalized template image, which is personalized to the subject based on a predetermined characteristic of the subject. The method further includes registering the subject personalized template image to the image of the subject. The method further includes performing statistical testing using the subject personalized template image registered to the image of the subject. A computing system (304) includes a memory (320) that stores a statistical testing module (320) and data (324). The computing system further includes a processor (318) that executes the one or more instructions, which causes the processor to: perform voxel-wise statistical testing of a functional image using a subject personalized template image for stereotactical normalization of the voxel-wise statistical testing.

Abstract: An imaging work station (20) includes one or more processors programmed to receive (170) an image depicting a distribution of a radiotracer in a brain or other region of interest. The radiotracer includes at least one of [18F]-Flutemetamol, [18F]-Florbetaben, and [18F]-Florbetapir which highlights amyloid deposits. The image and a template or an MRI image of the region of interest which includes a segmented anatomical feature, such as gray matter, are registered (180) to a common space. A volume representation of the image which depicts the distribution of the radiotracer in the segmented gray matter and suppresses the radiotracer outside of the segmented anatomical feature in white matter is extracted (210).

Abstract: A system and method directed to receiving a first data set corresponding to patient data at a first time, receiving a second data set corresponding to patient data at a second time, segmenting a first region of interest in the first data set and a second region of interest in the second data set, the first and second regions corresponding to one another and aligning the first region of interest with the second region of interest to highlight a first contour indicating a change in size, shape and orientation between the first and second regions of interest.

Abstract: A system (100) for displaying a multi-dimensional image and an annotation located therein, the system comprising receiving means (110) for receiving: the multi-dimensional image, the annotation, and representation data associated with the annotation, the representation data being indicative of a preferred representation of the multi-dimensional image and the annotation located therein; display means (130) for displaying an initial representation (300) of the multi-dimensional image and the annotation located therein; input means (120) for enabling a user to provide a visualization request when the initial representation shows at least a first part (310) of the annotation; and the display means (130) being arranged for, after receiving the visualization request, displaying the preferred representation (400) of the multi-dimensional image and the annotation located therein in accordance with the representation data, the preferred representation showing at least a second part (410) of the annotation, the second

Abstract: A measurement apparatus (800) to measure cortical thickness, the measurement apparatus may include at least one controller (810) which may be configured to: obtain magnetic resonance (MR) scan information of a region-of-interest of at least a portion of a cerebral cortex of a subject; form first, second and third meshes each comprising a plurality of points situated apart from each other, the first and third meshes being situated at inner and outer cortical boundary layers, respectively, of the cerebral cortex and the second mesh being situated between the first and third meshes; and/or for each of a plurality of points of the second mesh: determine a closest point of the first mesh and a closest point of the third mesh, determine a distance between the corresponding closest point of the first mesh and the corresponding closest point of the third mesh, said distance being corresponding with a cortical thickness.

Abstract: A medical system (10) and method detects amyloid brain plaque. A positron emission tomography (PET) image of a brain is received. The PET image is generated from a radiotracer binding to amyloid brain plaque. A cortical profile is generated from the PET image. The cortical profile describes cortical tracer uptake to varying projection depths inside the cortex of the brain. The PET image is quantitatively assessed using the cortical profile and/or at least a portion of the cortical profile is displayed.

Abstract: A system (100) and method is provided for performing a model-based segmentation of an anatomical structure in a medical image of a patient. The medical image (022) is accessed. Moreover, model data (162) is provided which defines a deformable model for segmenting the type of anatomical structure. The model-based segmentation of the anatomical structure is performed by adapting the deformable model to the anatomical structure in the medical image using an adaptation technique.

Abstract: A system and method directed to receiving a first data set corresponding to patient data at a first time, receiving a second data set corresponding to patient data at a second time, segmenting a first region of interest in the first data set and a second region of interest in the second data set, the first and second regions corresponding to one another and aligning the first region of interest with the second region of interest to highlight a first contour indicating a change in size, shape and orientation between the first and second regions of interest.

Abstract: A system and method including adapting a symmetric model representing anatomical structures of the brain, the model corresponding to a brain scan image, transforming first and second points provided on first and second hemispheres of the brain and computing, based on the transformation, a patient-specific symmetric anatomical model of the brain.

Abstract: An apparatus and related method for image viewing. The apparatus (V) allows to store, learn and remember preferred user views ?1-M for each anatomical structure F1-FN of interest. In any new image, the apparatus (V) affords automatically generating the preferred by the user for one or more of the structures (F1-FN) by a simple user input operation such as clicking with a mouse (PT) on any position within the displayed structure of interest (F1-FN).

Abstract: Generating a patient image collective (34) includes receiving a plurality of candidate images (20) and associated data. At least one inclusion/exclusion rule (44) is applied to the plurality of candidate images and associated data which results in subsets of candidate images (32). The candidate images are tested which result in at least one quality measure (40). The at least one quality measure (40) and associated candidate images are reviewed. The at least one inclusion/exclusion rule (44) is refined based on the reviewed at least one quality measure (40) by at least one of: adding a rule, modifying a rule, deleting a rule, removing a candidate image; and adding a candidate image. The steps of applying the at least one inclusion/exclusion rule through refining the at least one inclusion/exclusion rule are repeated until an optimized collective of images is generated based on a collective size and the at least one quality measure (40). The generated collective is outputted to a data store (34).

Abstract: Generating a patient image collective (34) includes receiving a plurality of candidate images (20) and associated data. At least one inclusion/exclusion rule (44) is applied to the plurality of candidate images and associated data which results in subsets of candidate images (32). The candidate images are tested which result in at least one quality measure (40). The at least one quality measure (40) and associated candidate images are reviewed. The at least one inclusion/exclusion rule (44) is refined based on the reviewed at least one quality measure (40) by at least one of: adding a rule, modifying a rule, deleting a rule, removing a candidate image; and adding a candidate image. The steps of applying the at least one inclusion/exclusion rule through refining the at least one inclusion/exclusion rule are repeated until an optimized collective of images is generated based on a collective size and the at least one quality measure (40). The generated collective is outputted to a data store (34).

Abstract: Image processing apparatus 110 for processing a medical image, comprising an input 120 for obtaining the medical image 122 and medical data 124, the medical image constituting a field of view in three-dimensional [3D] patient data, and the medical data showing an anatomical context of a content of the field of view, an output 130 for providing an output image 160 comprising the medical image and a visualization of the medical data, the medical data constituting non-patient specific medical data, and the imaging processing apparatus further comprising a processor 140 for (i) performing an image alignment between the medical image and the medical data for obtaining a transformation providing a position of the content with respect to its anatomical context, and (ii) using the transformation for establishing a graphical representation of the field of view in the visualization of the medical data at said position.

Abstract: An imaging work station (20) includes one or more processors programmed to receive (170) an image depicting a distribution of a radiotracer in a brain or other region of interest. The radiotracer includes at least one of [18F]-Flutemetamol, [18F]-Florbetaben, and [18F]-Florbetapir which highlights amyloid deposits. The image and a template or an MRI image of the region of interest which includes a segmented anatomical feature, such as gray matter, are registered (180) to a common space. A volume representation of the image which depicts the distribution of the radiotracer in the segmented gray matter and suppresses the radiotracer outside of the segmented anatomical feature in white matter is extracted (210).

Abstract: Image processing system 100 for enabling a user to navigate through image data having at least three spatial dimensions by displaying views 155 of the image data, the image processing system comprising an image device 110 comprising a display 130 for displaying the views of the image data and an orientation sensor 120 for measuring an orientation of the image device with respect to a reference orientation for providing rotation data 125 indicative of a device rotation of the image device, means 140 for N establishing a center of rotation in the image data, and an image processor 150 for establishing the views of the image data in relation to the device rotation by, for establishing a current view, (i) receiving the rotation data from the orientation sensor, (ii) establishing a view rotation in relation to the device rotation, and (iii) establishing the current view in dependence on the view rotation around the center of rotation with respect to a reference view.

Abstract: Cache controller (120) for use in a system (180) comprising an image client (100) and an image server (140), the image client enabling a user to navigate through image data having at least three spatial dimensions by displaying views of the image data that are obtained from the image server in dependence on navigation requests of the user, and the cache controller comprising a processor (122) configured for obtaining content data indicative of a content shown in a current view of the image client (100), the current view representing a first viewpoint in the three spatial dimensions of the image data, the processor being further configured for predicting a view request of the image client in dependence on the content data, the view request corresponding to a view representing a second viewpoint in the three spatial dimensions of the image data, and a communication means (124) for obtaining the view from the image server in dependence on the view request, and for caching the view in a cache (130).

Abstract: A system (100) for displaying a multi-dimensional image and an annotation located therein, the system comprising receiving means (110) for receiving: the multi-dimensional image, the annotation, and representation data associated with the annotation, the representation data being indicative of a preferred representation of the multi-dimensional image and the annotation located therein; display means (130) for displaying an initial representation (300) of the multi-dimensional image and the annotation located therein; input means (120) for enabling a user to provide a visualization request when the initial representation shows at least a first part (310) of the annotation; and the display means (130) being arranged for, after receiving the visualization request, displaying the preferred representation (400) of the multi-dimensional image and the annotation located therein in accordance with the representation data, the preferred representation showing at least a second part (410) of the annotation, the second

Abstract: A scanner (10) is used to provide images for automated diagnoses of neurodegenerative diseases, such as Alzheimers disease. The images are registered (90) to a template (78). The aligned image is analyzed (60) in relation to reference image data (76, 80) which has been registered to the template which is contained in a knowledge maintenance engine (70) for similar patterns of hypo-intensity that would indicate (in the case of an FDG tracer) reduced glucose uptake in the brain. The most appropriate reference images for the analysis of the present study are chosen by a filter (74). The present study is then given a dementia score (84) as a diagnostic feature vector that indicates to a clinician the type and severity of the ailment based on the analysis. The scanner (10) can produce PET or other metabolic and MR images for diagnosis. The MR can be used to measure blood flow rate into the brain. From the blood flow rate and the metabolic image, tracer, e.g.

Abstract: When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and a type of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the user can adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' brain scan image.

Abstract: When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and a type of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the user can adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' brain scan image.