Abstract: A cortical malformation identification method includes quantitatively evaluating, using a processor of a computer that includes the processor and a memory, digital image data from a magnetic resonance imaging (MRI) scan on a cerebral cortex to produce quantified scan data. The method also includes automatically detecting a cortical malformation based on the quantified scan data. An image of the cerebral cortex may be color-coded so that the cortical malformation is shown in a different color than the remainder of the cerebral cortex in the image, based on the quantified scan data. Additionally or alternatively, a 3-dimensional representation of the cerebral cortex may be mapped to the quantified scan data to produce a mapped image of the cerebral cortex including the detected cortical malformation.

Abstract: A method (10) that encodes electrode locations to a mean scalp mesh for adaptation to subsequent image scans.

Abstract: Methods and systems that provide quantitative assessments of in vivo thermal treatments, such as ablations, during image-guided surgeries using a high-resolution pre-operative MRI image segmented with a shape constrained and deformable mesh representations of brain structures and generating 3-D visualizations of thermally treated volumes during the thermal treatment that can provide near real time visual and quantitative feedback to a clinician.

Abstract: Methods and systems that identify an intrabody orientation of a directional medical device, such as a deep brain stimulation (DBS) lead, use a mesh model. The mesh model is a shape-constrained trained model of fused post-operative MRI and CT image data of brains from a set of patients defined by intensity of artifact patterns corresponding to a passive orientation marker on a physical device.

Abstract: Systems and methods for obtaining anatomical-structure-specific activation data in a brain of a patient are provided. In an embodiment, a method for obtaining anatomical-structure-specific activation data in a brain of a patient includes receiving magnetic resonance (MR) data of the brain obtained by use of a magnetic resonance imaging (MRI) device; segmenting the MR data of the brain to delineate a plurality of geometries, each of the plurality of geometries corresponding to a respective anatomical structure in the brain; receiving functional magnetic resonance (fMRI) data of the brain obtained by use of an MRI device; aligning the MR data and the fMRI data; determining a plurality of activation levels, each of the activation levels corresponding to respective delineated geometries based on the aligned MR data and fMRI data; and outputting a graphical representation of a dynamic activity in the brain corresponding to the delineated geometries of the anatomical structures.

Abstract: A method (26) that tessellates a cortical surface of a brain with a plurality of dipole patches, wherein a quantity of the plurality of dipole patches is variable and dependent upon a head size.

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 MRI 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: In one embodiment, a method that determine parameters corresponding to shape and volume of the one or more brain structures from the one or more meshes (36) and provides the parameters to a classifier to estimate a probability of a brain abnormality based on the parameters.

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: A method (10) that encodes electrode locations to a mean scalp mesh for adaptation to subsequent image scans.

Abstract: Systems and methods for obtaining anatomical-structure-specific activation data in a brain of a patient are provided. In an embodiment, a method for obtaining anatomical-structure-specific activation data in a brain of a patient includes receiving magnetic resonance (MR) data of the brain obtained by use of a magnetic resonance imaging (MRI) device; segmenting the MR data of the brain to delineate a plurality of geometries, each of the plurality of geometries corresponding to a respective anatomical structure in the brain; receiving functional magnetic resonance (fMRI) data of the brain obtained by use of an MRI device; aligning the MR data and the fMRI data; determining a plurality of activation levels, each of the activation levels corresponding to respective delineated geometries based on the aligned MR data and fMRI data; and outputting a graphical representation of a dynamic activity in the brain corresponding to the delineated geometries of the anatomical structures.

Abstract: A seizure characterization method includes correlating locations of electrodes placed around a brain and used to produce sequential electroencephalography (EEG) signals with a three-dimensional anatomical brain model derived from magnetic resonance imaging (MRI). The sequential EEG signals are modelled from the electrodes placed around the brain in three dimensions using cortical and sub-cortical brain regions included in the brain model to define constraints for the numerical solution. Amounts of the sequential EEG signals are quantified in three dimensions relative to the brain regions included in the brain model. The method also includes establishing, based on the quantifying, at least one propagation pattern of the sequential EEG signals in time relative to the brain regions in the brain model.

Abstract: Systems and methods for evaluating an anatomical structure in a brain of a subject are provided. In an embodiment, a system for evaluating an anatomical structure in a brain of a subject includes a computing device in communication with a magnetic resonance imaging (MRI) device. The computing device operable to determine an abnormality in the anatomical structure by comparing a test activation level within a geometry of the anatomical structure to data in a normative database, and output, to a display device, a graphical representation of the abnormality in the anatomical structure. The test activation level is determined by aligning functional magnetic resonance imaging (fMRI) data obtained by use of the MRI device and the geometry of the anatomical structure. The geometry of the anatomical structure is delineated based on segmentation of magnetic resonance (MR) data obtained by use of the MRI device.

Abstract: Systems and methods for magnetic resonance (MR) examination are provided.

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: 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 cortical malformation identification method includes quantitatively evaluating, using a processor of a computer that includes the processor and a memory, digital image data from a magnetic resonance imaging (MRI) scan on a cerebral cortex to produce quantified scan data. The method also includes automatically detecting a cortical malformation based on the quantified scan data. An image of the cerebral cortex may be color-coded so that the cortical malformation is shown in a different color than the remainder of the cerebral cortex in the image, based on the quantified scan data. Additionally or alternatively, a 3-dimensional representation of the cerebral cortex may be mapped to the quantified scan data to produce a mapped image of the cerebral cortex including the detected cortical malformation.

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: Systems and methods for evaluating an anatomical structure in a brain of a subject are provided. In an embodiment, a system for evaluating an anatomical structure in a brain of a subject includes a computing device in communication with a magnetic resonance imaging (MRI) device. The computing device operable to determine an abnormality in the anatomical structure by comparing a test activation level within a geometry of the anatomical structure to data in a normative database, and output, to a display device, a graphical representation of the abnormality in the anatomical structure. The test activation level is determined by aligning functional magnetic resonance imaging (fMRI) data obtained by use of the MRI device and the geometry of the anatomical structure. The geometry of the anatomical structure is delineated based on segmentation of magnetic resonance (MR) data obtained by use of the MRI device.

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.