Abstract: Image processing method or apparatus (IP) to transform a 3D image data set (DS) into a visually protected one (DSX). The 3D image set includes an object region (OR) and a background region (BR) that defines s silhouette of an imaged object (P). An inadvertent or malicious direct volume rendering of the silhouette (IF) of the object is prevented by applying a randomization operation to at least the background region (BR).

Abstract: A system and method are provided for brain tissue classification, which involves applying an automated tissue classification technique to an image of a brain based on a prior probability map, thereby obtaining a tissue classification map of the brain. A user is enabled to, using a user interaction subsystem, provide user feedback which is indicative of a) an area of misclassification in the tissue classification map and b) a correction of the misclassification. The prior probability map is then adjusted based on the user feedback to obtain an adjusted prior probability map, and the automated tissue classification technique is re-applied to the image based on the adjusted prior probability map. An advantage over a direct correction of the tissue classification map may be that the user does not need to indicate the area of misclassification or the correction of the misclassification with a highest degree of accuracy. Rather, it may suffice to provide an approximate indication thereof.

Abstract: A system and method are provided for interactive editing of a mesh which has been applied to a three-dimensional (3D) image to segment an anatomical structure shown therein. To facilitate the interactive editing of the applied mesh, a view of the 3D image is generated which shows a mesh part to be edited, with the view being established based on a local orientation of the mesh part. Advantageously, the view may be generated to be substantially orthogonally to the mesh part, or to a centerline of the anatomical structure which is determined as a function of the mesh part. Accordingly, an orthogonal view is established which facilitates the user in carrying out the editing action with respect to the mesh part. It is therefore not needed for the user to manually navigate through the 3D image to obtain a view which is suitable for mesh editing, which is typically time consuming.

Abstract: The present invention relates to a medical instrument for automatically detecting affected regions in an examination area of a subject comprising: a memory containing machine executable instructions; and a processor for controlling the medical instrument, wherein execution of the machine executable instructions causes the processor to control the instrument to: obtain a first anatomical image of the examination area and a first image of fibers of the examination area, wherein a first parameter and a second parameter describe characteristics of the first anatomical image and the first image of fibers respectively; segment the first anatomical image into a plurality of segments indicating respective tissues and/or structures in the examination area; identify first lesions in the segmented first anatomical image; use values of the first and/or second parameters for determining seed points in the identified first lesions for a tracking algorithm for tracking first fibers in the first image of fibers.

Abstract: The present invention provides for means for linking breast lesion locations across imaging studies. In particular, a generic three-dimensional representation of the female breast is used. Automatic translation of the lesion location into standard clinical terminology and aligning the breast model with individual patient images is comprised. Moreover, a mechanism for linking image locations showing a lesion to a location in the breast model is presented. If desired, a region of interest can be calculated by a region of interest definition module that predicts a region of interest of a known lesion in terms of the breast model representation in a new imaging study.

Abstract: A method includes determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The method further includes registering first volumetric scan image data and second volumetric scan image data based on the registration transform. The method further includes generating registered image data. A system (100) includes a pre-scan registerer (122) that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The system further includes a volume registerer (126) that registers first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

Abstract: A method and system are provided for visualizing a surgical path for a surgical tool. The method comprises a step of receiving anatomical information about a position of at least one anatomical structure in a region to undergo surgery, geometric information describing the surgical path and at least one safety margin defining a minimal distance between the surgical tool and the anatomical structure. The method further comprises defining a critical segment of the surgical path, in which critical segment a distance to the anatomical structure is smaller than the safety margin. Then a graphical representation of the surgical path is provided, wherein the critical segment is highlighted.

Abstract: A system and method are provided for interactive editing of a mesh which has been applied to a three-dimensional (3D) image to segment an anatomical structure shown therein. To facilitate the interactive editing of the applied mesh, a view of the 3D image is generated which shows a mesh part to be edited, with the view being established based on a local orientation of the mesh part. Advantageously, the view may be generated to be substantially orthogonally to the mesh part, or to a centerline of the anatomical structure which is determined as a function of the mesh part. Accordingly, an orthogonal view is established which facilitates the user in carrying out the editing action with respect to the mesh part. It is therefore not needed for the user to manually navigate through the 3D image to obtain a view which is suitable for mesh editing, which is typically time consuming.

Abstract: A system 100 for enabling interactive annotation of an image 102, comprising a user input 160 for receiving a placement command 162 from a user, the placement command being indicative of a first placement location of a marker 140 in the image 102, and a processor 180 arranged for (i) applying an image processing algorithm to a region 130 in the image, the region being based on the first placement location, and the image processing algorithm being responsive to image portions which visually correspond to the marker 140 for establishing a plurality of match degrees between, on the one hand, the marker, and, on the other hand, a plurality of image portions within the region, (ii) establishing a second placement location in dependence on the plurality of match degrees and the respective plurality of image portions for matching the marker 140 to the region in the image, and (iii) placing the marker 140 at the second placement location in the image 102.

Abstract: A system and method are provided for brain tissue classification, which involves applying an automated tissue classification technique to an image of a brain based on a prior probability map, thereby obtaining a tissue classification map of the brain. A user is enabled to, using a user interaction subsystem, provide user feedback which is indicative of a) an area of misclassification in the tissue classification map and b) a correction of the misclassification. The prior probability map is then adjusted based on the user feedback to obtain an adjusted prior probability map, and the automated tissue classification technique is re-applied to the image based on the adjusted prior probability map. An advantage over a direct correction of the tissue classification map may be that the user does not need to indicate the area of misclassification or the correction of the misclassification with a highest degree of accuracy. Rather, it may suffice to provide an approximate indication thereof.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

Abstract: The present invention relates to medical image editing. In order to facilitate the medical image editing process, a medical image editing device (50) is provided that comprises a processor unit (52), an output unit (54), and an interface unit (56). The processor unit (52) is configured to provide a 3D surface model of an anatomical structure of an object of interest. The 3D surface model comprises a plurality of surface sub-portions. The surface sub-portions each comprise a number of vertices, and each vertex is assigned by a ranking value. The processor unit (52) is further configured to identify at least one vertex of vertices adjacent to the determined point of interest as an intended vertex. The identification is based on a function of a detected proximity distance to the point of interest and the assigned ranking value. The output unit (54) is configured to provide a visual presentation of the 3D surface model.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

Abstract: A method includes displaying an iconic image of the human body and a list of predetermined anatomical regions. The method further includes displaying, in response to a user selected anatomical region, a scan box over a sub-portion of the iconic image. The method further includes receiving an input indicative of at least one of a scan box location of interest or a scan box geometry of interest, with respect to the anatomical region, of the first user. The method further includes at least one of re-locating or changing a geometry of the first initial scan box, in response thereto, creating a first user defined scan box for the first user. The method further includes creating a first transformation between a first template image representative of the selected anatomical region and the iconic image with the first user defined scan box for the first user, and storing the first transformation.

Abstract: A method, system and program product are provided for planning an intervention procedure in a body lumen. A CT scan of the body lumen is performed. A virtual rendering is created of the inside of the body lumen corresponding to an interventional camera image. Then a virtual tape corresponding to a planned path for the intervention procedure is projected onto a wall of the body lumen. The virtual tape is projected onto the lumen wall, which is relatively distant from the camera point on the virtual rendering, so the tape does not appear to oscillate like a central thread. Also, since the virtual tape is located on the lumen wall, it does not occlude the center of the lumen, allowing a user to better visualize the lumen during planning, during fly through, and even during an actual intervention.

Abstract: A digital image (40) comprises pixels with intensities relating to different energy levels.

Abstract: The invention relates to a scan region determining apparatus (12) for determining a scan region of a subject to be scanned by a scanning system (10) like a computed tomography system. A spatial transformation defining a registration of an overview image and a template image with respect to each other is determined, wherein initially the overview image and the template image are registered by using an element position indicator being indicative of a position of an element of the subject with respect to the overview image. A template scan region is defined with respect to the template image, wherein a final scan region is determined by projecting the template scan region onto the overview image by using the determined spatial transformation. The registration and thus the determination of the spatial transformation are very robust, which improves the quality of determining the final scan region.

Abstract: A system for displaying a plurality of registered images is disclosed. A first viewport unit displays a representation of a first image dataset in a first viewport. A second viewport unit displays a representation of a second image dataset in a second viewport. A position indication unit enables a user to indicate a position in the first dataset displayed in the first viewport, to obtain a user-indicated position. A corresponding position determining unit determines a position in the second image dataset corresponding to the user-indicated position, to obtain a corresponding position in the second image dataset, based on correspondence information mapping positions in the first image dataset to corresponding positions in the second image dataset. The second viewport unit displays an indication of the corresponding position in the second viewport.

Abstract: A method includes determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The method further includes registering first volumetric scan image data and second volumetric scan image data based on the registration transform. The method further includes generating registered image data. A system (100) includes a pre-scan registerer (122) that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The system further includes a volume registerer (126) that registers first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.