Abstract: Systems and methods for automated voxel positioning in magnetic resonance spectroscopy (“MRS”) are provided. In some aspects, a method includes receiving magnetic resonance (“MR”) imaging data acquired from a subject using an MR imaging system and registering the MR imaging data to an atlas having a pre-defined volume of interest (“VOI”), or segmenting a region of interest (“ROI”) directly from the MR data. The method also includes generating registration parameters based on the registration, and computing a transformed VOI using the pre-defined VOI in the atlas and the registration parameters. Alternatively, the VOI may be obtained by directly estimating it from the ROI.

Abstract: Systems and methods for automated voxel positioning in magnetic resonance spectroscopy (“MRS”) are provided. In some aspects, a method includes receiving magnetic resonance (“MR”) imaging data acquired from a subject using an MR imaging system and registering the MR imaging data to an atlas having a pre-defined volume of interest (“VOI”), or segmenting a region of interest (“ROI”) directly from the MR data. The method also includes generating registration parameters based on the registration, and computing a transformed VOI using the pre-defined VOI in the atlas and the registration parameters. Alternatively, the VOI may be obtained by directly estimating it from the ROI.

Abstract: A method for generating a positron emission tomography (PET) attenuation correction map from magnetic resonance (MR) images includes segmenting a 3-dimensional (3D) magnetic resonance (MR) whole-body image of a patient into low-signal regions, fat regions, and soft tissue regions; classifying the low-signal regions as either lungs, bones, or air by identifying lungs, identifying an abdominal station, and identifying a lower body station; and generating an attenuation map from the segmentation result by replacing the segmentation labels with corresponding representative attenuation coefficients.

Abstract: A method for generating a positron emission tomography (PET) attenuation correction map from magnetic resonance (MR) images includes segmenting a 3-dimensional (3D) magnetic resonance (MR) whole-body image of a patient into low-signal regions, fat regions, and soft tissue regions; classifying the low-signal regions as either lungs, bones, or air by identifying lungs, identifying an abdominal station, and identifying a lower body station; and generating an attenuation map from the segmentation result by replacing the segmentation labels with corresponding representative attenuation coefficients.

Abstract: A collision detection method for polygonal objects using OpenGL is provided, comprising dividing a surface of each object into a set of axis aligned bounding boxes (AABB) to build an AABB tree, selecting an object among the plurality of polygonal objects as a reference object, defining a global bounding box of the reference object, detecting first bounding boxes of the plurality of polygonal objects that intersect the global bounding box of the reference object, and determining intersections for each polygon of the reference object with all polygons of the plurality of polygonal objects.

Abstract: A collision detection method for polygonal objects using OpenGL is provided, comprising dividing a surface of each object into a set of axis aligned bounding boxes (AABB) to build an AABB tree, selecting an object among the plurality of polygonal objects as a reference object, defining a global bounding box of the reference object, detecting first bounding boxes of the plurality of polygonal objects that intersect the global bounding box of the reference object, and determining intersections for each polygon of the reference object with all polygons of the plurality of polygonal objects.