Abstract: A method of generating a modified X-ray image includes obtaining an X-ray image, obtaining a CT image corresponding to the X-ray image, determining a mapping between the X-ray image and the CT image, identifying a structure of interest in the CT image, generating an attenuation map from the CT image, the attenuation map indicative of attenuation due to the structure of interest or everything but the structure of interest on the X-ray image, and generating the modified X-ray image by subtracting the attenuation map from the X-ray image.

Abstract: Presented are concepts for initialising a model for model-based segmentation of an image which use specific landmarks (e.g. detected using other techniques) to initialize the segmentation mesh. Using such an approach, embodiments need not be limited to predefined model transformations, but can initialise a segmentation mesh with arbitrary shape. In this way, embodiments may provide for an image segmentation algorithm that not only delivers a robust surface-based segmentation result but also does so for strongly varying target structure variations (in terms of shape).

Abstract: Presented are concepts for displaying medical images. One such concept generates transformation data by mapping image data of a medical image to a location in an anatomical atlas and by determining a transfer function for transforming image data of the medical image for display. The transfer function is then associated with the location in the anatomical atlas. A medical image can then be displayed by identifying a transfer function associated with a selected location in the anatomical atlas. The identified transfer function is applied to image data of a medical image that is mapped to the selected location in the anatomical atlas so as to obtain transformed image data. A transformed version of the medical image is then displayed based on the transformed image data.

Abstract: A radiology viewer includes at least one electronic processor (10, 20), at least one display (12), and at least one user input device (14, 16, 18). The display shows at least a portion of a radiology image (30) in an image window (40), and at least a portion of a radiology report (32) in a report window (42). A selection is received of an anatomical feature shown in the image window, and a corresponding passage of the radiology report is identified and highlighted in the report window. A selection is received of a passage of the radiology report shown in the report window, and a corresponding anatomical feature of the at least one radiology image is identified and highlighted in the image window. The highlighting operations use image anatomical feature tags and report clinical concept tags generated using a medical ontology (56) and an anatomical atlas (62).

Abstract: A system and a method are provided for enabling a user to interactively navigate through a set of slice images, the set of slice images jointly representing an image volume showing an anatomical structure of a patient. A user may be enabled to switch from a static viewing mode to a navigation mode based on navigation commands received from a user input device operable by the user. A display processor may be configured for, in the static viewing mode, generating an output image comprising one slice image of the set of slice images. The display processor may be configured for, in the navigation mode, replacing the said one slice image in the output image by a volume rendering of a slab of the image volume, the slab comprising more than one slice image. The system and method thus selectively switch to volume rendering, namely during navigation, whereas in a static (i.e., non-navigation) viewing mode, a slice image is shown.

Abstract: System and related method to visualize image data. The system comprises an input port (IN) for receiving i) image data comprising a range of intensity values converted from signals acquired by an imaging apparatus in respect of an imaged object, and ii) a definition of a first transfer function configured to map a data interval within said range of said intensity values to an image interval of image values. A transition region identifier (TRI) identifies from among intensity values outside said data interval, one or more transition intensity values representative of a transition in composition and/or configuration of said object or of a transition in respect of a physical property in relation to said object. A transfer function generator (TFG) generates for said intensity values outside said data interval a second transfer function. The second transfer function is non-linear and has a respective gradient that is locally maximal around said transition intensity values.

Abstract: A symmetric model representing anatomical structures of the brain is adapted to a brain scan image with a transform. First and second points provided on first and second hemispheres of the brain image and a patient-specific symmetric anatomical model of the brain is computed based on the transformation.

Abstract: A medical imaging system (5) includes a workstation (20), a coarse segmenter (30), a fine segmenter (32), and an enclosed tissue identification module (34). The workstation (20) includes at least one input device (22) for receiving a selected location as a seed in a first contrasted tissue type and a display device (26) which displays a diagnostic image delineating a first segmented region of a first tissue type and a second segmented region of a second contrasted tissue type and identified regions which include regions fully enclosed by the first segmented region as a third tissue type. The coarse segmenter (30) grows a coarse segmented region of coarse voxels for each contrasted tissue type from the seed location based on a first growing algorithm and a growing fraction for each contrasted tissue type.

Abstract: A system and a method are provided for enabling a user to interactively navigate through a set of slice images, the set of slice images jointly representing an image volume showing an anatomical structure of a patient. A user may be enabled to switch from a static viewing mode to a navigation mode based on navigation commands received from a user input device operable by the user. A display processor may be configured for, in the static viewing mode, generating an output image comprising one slice image of the set of slice images. The display processor may be configured for, in the navigation mode, replacing the said one slice image in the output image by a volume rendering of a slab of the image volume, the slab comprising more than one slice image. The system and method thus selectively switch to volume rendering, namely during navigation, whereas in a static (i.e., non-navigation) viewing mode, a slice image is shown.

Abstract: A device for segmenting an image of a subject (36), includes a data interface for receiving an image of the subject (36), which image depicts a structure of said subject (36). A translation unit translates a user-initiated motion of an image positioner into a first contour (38) surrounding said structure. A motion parameter registering unit registers a motion parameter of said user-initiated motion to said first contour (38). The motion parameter includes a speed and/or an acceleration of an image positioner. An image control point unit distributes a plurality of image control points (40) on the first contour with a density decreasing with the motion parameter. A segmentation unit segments the image by determining a second contour (44) within the first contour based on the plurality of image control points (40). The segmentation unit is configured to use one or more segmentation functions.

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: A method includes obtaining a single training image from a set of training images in a data repository. The method further includes generating an initial tissue class atlas based on the obtained single training image. The initial tissue class atlas includes two or more different tissue class images corresponding to two or more different tissue classes. The method further includes registering the remaining training images of the set of training images to the initial tissue class atlas. The method further includes generating a quality metric for each of the registered images. The method further includes evaluating the quality metric of each of the registered image with a predetermined evaluation criterion. The method further includes identifying a sub-set of images from the set of training images that satisfy the evaluation criterion. The method further includes generating a subsequent tissue class atlas based on the identified sub-set of the set of training images.

Abstract: System and related method to visualize image data. The system comprises an input port (IN) for receiving i) image data comprising a range of intensity values converted from signals acquired by an imaging apparatus in respect of an imaged object, and ii) a definition of a first transfer function configured to map a data interval within said range of said intensity values to an image interval of image values. A transition region identifier (TRI) identifies from among intensity values outside said data interval, one or more transition intensity values representative of a transition in composition and/or configuration of said object or of a transition in respect of a physical property in relation to said object. A transfer function generator (TFG) generates for said intensity values outside said data interval a second transfer function. The second transfer function is non-linear and has a respective gradient that is locally maximal around said transition intensity values.

Abstract: The present invention relates to a device for segmenting an image of a subject (36), comprising a data interface for receiving an image of said subject (36), said image depicting a structure of said subject (36), a translation unit for translating a user-initiated motion of an image positioner means into a first contour (38) surrounding said structure, a motion parameter registering unit for registering a motion parameter of said user-initiated motion to said first contour (38), said motion parameter comprising a speed and/or an acceleration of said image positioner means, an image control point unit for distributing a plurality of image control points (40) on said first contour with a density decreasing with said motion parameter, and a segmentation unit for segmenting said image by determining a second contour (44) within said first contour based on said plurality of image control points (40), said segmentation unit being configured to use one or more segmentation functions.

Abstract: A medical imaging system (5) includes a workstation (20), a coarse segmenter (30), a fine segmenter (32), and an enclosed tissue identification module (34). The workstation (20) includes at least one input device (22) for receiving a selected location as a seed in a first contrasted tissue type and a display device (26) which displays a diagnostic image delineating a first segmented region of a first tissue type and a second segmented region of a second contrasted tissue type and identified regions which include regions fully enclosed by the first segmented region as a third tissue type. The coarse segmenter (30) grows a coarse segmented region of coarse voxels for each contrasted tissue type from the seed location based on a first growing algorithm and a growing fraction for each contrasted tissue type.

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 medical imaging system (5) includes a workstation (20), a coarse segmenter (30), a fine segmenter (32), and an enclosed tissue identification module (34). The workstation (20) includes at least one input device (22) for receiving a selected location as a seed in a first contrasted tissue type and a display device (26) which displays a diagnostic image delineating a first segmented region of a first tissue type and a second segmented region of a second contrasted tissue type and identified regions which include regions fully enclosed by the first segmented region as a third tissue type. The coarse segmenter (30) grows a coarse segmented region of coarse voxels for each contrasted tissue type from the seed location based on a first growing algorithm and a growing fraction for each contrasted tissue type.

Abstract: A method includes obtaining a single training image from a set of training images in a data repository. The method further includes generating an initial tissue class atlas based on the obtained single training image. The initial tissue class atlas includes two or more different tissue class images corresponding to two or more different tissue classes. The method further includes registering the remaining training images of the set of training images to the initial tissue class atlas. The method further includes generating a quality metric for each of the registered images. The method further includes evaluating the quality metric of each of the registered image with a predetermined evaluation criterion. The method further includes identifying a sub-set of images from the set of training images that satisfy the evaluation criterion. The method further includes generating a subsequent tissue class atlas based on the identified sub-set of the set of training images.

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 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.