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: Devices, systems, methods for validating ablation results in a patient's brain are provided. In some embodiments, the method for validating ablation result in a patient's brain includes obtaining magnetic resonance (MR) data of the patient's brain, by use of a magnetic resonance imaging (MRI) device; obtaining first imaging data of the patient's brain, by use of the MRI device; extracting, by use of computing device in communication with the MM device, first fiber tracts passing through an anatomy in the patient's brain based on the first imaging data; obtaining, by use of the MRI device, second imaging data of the patient's brain after ablation of the anatomy in the patient's brain has started; extracting second fiber tracts passing through the anatomy in the patient's brain based on the second imaging data; and outputting a graphical representation of a comparison between the first fiber tracts and the second fiber tracts.

Abstract: Treatment trajectory guidance systems and methods are provided. In one embodiment, the method for treatment trajectory guidance in a patient's brain includes obtaining a three- dimensional (3D) brain model that includes a model of an anatomy, the model of the anatomy including a plurality of feature points; modifying the 3D brain model based on magnetic resonance (MR) data of the patient's brain from a magnetic resonance imaging (MRI) device to obtain a plurality of modified feature points on a modified model of the patient's anatomy in the patient's brain; displaying on a display a first planned trajectory for treating the patient's anatomy based on the plurality of modified feature points; and displaying, on the display, a first estimated treatment result for the first planned trajectory.

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: 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 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: 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 system, apparatus and method for mesh registration including an extraction of a preoperative anatomical mesh from a preoperative anatomical image based on a base topology of an anatomical mesh template, an extraction of an intraoperative anatomical mesh from an intraoperative anatomical image based on a preoperative topology of the preoperative anatomical mesh derived from the base topology of an anatomical mesh template, and a registration of the preoperative anatomical image and the intraoperative anatomical image based on a mapping correspondence between the preoperative anatomical mesh and the intraoperative anatomical mesh established by an intraoperative topology of the intraoperative anatomical mesh derived from the preoperative topology of the preoperative anatomical mesh.

Abstract: An imaging apparatus for imaging an object includes a geometric relation determination unit configured to determine a geometric relation between first and second images of the object. A marker determination unit configured to determine corresponding marker locations in the first and second images and marker appearances based on the geometric relation such that the marker appearances of a first marker to be located at a first location in the first image and of a second marker to be located at a second corresponding location in the second image are indicative of the geometric relation. The images with the markers at the respective corresponding locations are shown on a display unit. Since the marker appearances are indicative of the geometric relation between the images, a comparative reviewing of the images can be facilitated, in particular, if they correspond to different viewing geometries.

Abstract: A MRSI system (100) includes a structure of interest identifier (206) that identifies a predetermined segmented structure in segmented MRI image data, a positioning rules bank (210) which stores rules for positioning a volume of interest with respect to the identified predetermined segmented structure of the segmented MRI image data, and a volume of interest generator (208) that positions the volume of interest with respect to the identified predetermined segmented structure based on one or more of the rules for positioning the volume of interest with respect to the identified predetermined segmented structure and generates a signal indicative thereof, wherein the signal is analyzed to determine a biochemical composition of a predetermined region of the structure of interest.

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 method for a mesh segmentation and a mesh registration involves an extraction of a preoperative anatomical mesh (51) from a preoperative anatomical image (50) based on a base topology of an anatomical mesh template (40), an extraction of an intraoperative anatomical mesh (61) from an intraoperative anatomical image (60) based on a preoperative topology of the preoperative anatomical mesh (51) derived from the base topology of an anatomical mesh template (40), and a registration of the preoperative anatomical image (50) and the intraoperative anatomical image (60) based on a mapping correspondence between the preoperative anatomical mesh (51) and the intraoperative anatomical mesh (61) established by an intraoperative topology of the intraoperative anatomical mesh (61) derived from the preoperative topology of the preoperative anatomical mesh (51).

Abstract: A system and method for automatic segmentation, performed by selecting a deformable model of an anatomical structure of interest imaged in a volumetric image, the deformable model formed of a plurality of polygons including vertices and edges, displaying the deformable model on a display, detecting a feature point of the anatomical structure of interest corresponding to each of the plurality of polygons and adapting the deformable model by moving each of the vertices toward the corresponding feature points until the deformable model morphs to a boundary of the anatomical structure of interest, forming a segmentation of the anatomical structure of interest.

Abstract: A medical system (50, 100) comprises at least one processor (32, 62, 120) programmed to receive patient-specific data of a patient. The patient-specific data includes at least one of: 1) image and/or map data; and 2) physiological data. The at least one processor (32, 62, 120) is further programmed to visually display at least some of the patient-specific data to a user of the medical system (50, 100) on a monitor (70, 128), and modulate a signal to convey data to the user using a sense other than sight. The signal is modulated based on at least one of: a parameter extracted from the patient-specific data; and a position of: 1) a displayed slice of an image and/or map of the patient-specific data; or 2) a device within the patient.

Abstract: A system for processing multi-subject volumes comprises a volume input (1) for receiving an input volume image dataset (13) comprising a plurality of subjects scanned simultaneously. A metadata input (2) receives metadata (15) relating to individual ones of the subjects. A subject finder (3) identifies a plurality of portions of the input volume image dataset (13), each portion comprising one of the subjects. A volume image dataset generator (4) generates a plurality of separate volume image datasets (16), each separate volume image dataset (7) comprising one of the portions of the input volume image dataset. A metadata handler (5) associates the metadata (15) relating to a subject with the separate volume image dataset (7) comprising the portion comprising the subject.

Abstract: A system and method for receiving a medical image, receiving an adaptation of a model of a physical structure, the adaptation relating to the medical image, determining an image quantity of the medical image at each of a plurality of vertices of the adaptation and aggregating the plurality of image quantities to determine an evaluation metric.

Abstract: The invention relates to an imaging apparatus for imaging an object. A geometric relation determination unit (10) determines a geometric relation between first and second images of the object, wherein a marker determination unit (14) determines corresponding marker locations in the first and second images and marker appearances based on the geometric relation such that the marker appearances of a first marker to be located at a first location in the first image and of a second marker to be located at a second corresponding location in the second image are indicative of the geometric relation. The images with the markers at the respective corresponding locations are shown on a display unit (16). Since the marker appearances are indicative of the geometric relation between the images, a comparative reviewing of the images can be facilitated, in particular, if they correspond to different viewing geometries.

Abstract: A MRSI system (100) includes a structure of interest identifier (206) that identifies a predetermined segmented structure in segmented MRI image data, a positioning rules bank (210) which stores rules for positioning a volume of interest with respect to the identified predetermined segmented structure of the segmented MRI image data, and a volume of interest generator (208) that positions the volume of interest with respect to the identified predetermined segmented structure based on one or more of the rules for positioning the volume of interest with respect to the identified predetermined segmented structure and generates a signal indicative thereof, wherein the signal is analyzed to determine a biochemical composition of a predetermined region of the structure of interest.

Abstract: An ultrasound system for planning a surgical implantation of a prosthetic aortic valve produces three dimensional images of the aortic root region of a patient. An electronic model of an aortic root is accessed and fitted to the aortic root in a three dimensional ultrasound image. Preferably the aortic root model exhibits closed contour cross-sections which are fitted to the endothelial lining of the aortic root in the ultrasound image. A medial axis of the fitted model is identified and radii measured from the medical axis to the border of the fitted model. The radii are joined to identify a surface forming a mesh model fitted to the aortic root anatomy of the patient. The shape and dimensions of the fitted model may be used to fabricate a custom prosthetic valve for aortic valve replacement.

Abstract: A system and method for identifying an abnormality of an anatomical structure. The system and method segments, using a processor, the anatomical structure imaged in a volumetric image of a plurality of control patients to produce a control segmentation of the anatomical structures of each of the control patients, obtains a normative dataset by extracting a statistical representation of a morphology of the control segmentations, segments the anatomical structure of a patient being analyzed for abnormalities to produce a patient segmentation and compares the patient segmentation to the normative dataset obtained from the control segmentations.