Abstract: A computer readable medium is provided embodying instructions executable by a processor to perform a method for sparse volume segmentation for 3D scan of a target. The method including learning prior knowledge, providing volume data comprising the target, selecting a plurality of key contours of the image of the target, building a 3D spare model of the image of the target given the plurality of key contours, segmenting the image of the target given the 3D sparse model, and outputting a segmentation of the image of the target.

Abstract: A fetal skeleton is rendered with medical diagnostic ultrasound. Ultrasound scans of fetal skeleton may acquire data at a rate sufficient to avoid some fetal movement artifacts as compared to magnetic resonance or computed tomography. To better visualize the fetal skeleton, the ultrasound data is used to segment the fetal bone from tissue. By extracting this information, a skeleton in three dimensions is determined. Information representing internal bone locations may be used for fetal bone imaging. Without repeating the segmentation and without adjustments for volume thickness, the skeleton may be visualized from different orientations. A volumetric or surface rendering is performed, allowing addition of lighting queues not available with MIP or other projection rendering free of segmentation. The lighting queues may better indicate actual size and orientation of bones relative to each other on the rendered image.

Abstract: Presegmentation or prior, pre-existing segmentation of an object obtained through other means will be presented for interactive editing of a segmented object in an image or volume. Prior segmentation will be seamlessly combined with graph cuts or the random walker methods. Editing of the presegmentation is possible, while maintaining the important property of both methods that an arbitrary segmentation may be achieved with enough interaction.

Abstract: A system and method for automatically determining the standard cardiac image views as defined by the American Heart Association from volumetric data of the chest including the heart. The system and method can be used by a health practitioner to quickly see the two dimensional views from which a diagnosis is generally made. The left ventricle is detected. Then the relative orientation of the right ventricle is determined and the standard cardiac views are determined.

Abstract: Motion of the heart during contrast enhancement is modeled at two hierarchical levels: global translation and local deformation. Large-scale, i.e., global, translational motion is identified using global template matching, while the local deformation of a portion of the object (e.g., the left ventricle where the object is a heart) is obtained using an adaptive local template matching scheme which adapts to the local edge distributions by varying the height and the width of the template as well as the location of the template followed by spatial regularization. To address the difficulty of rapid intensity changes across the image sequence as the contrast agent perfuse into the tissue, an edge-based similarity measure is used for template matching.

Abstract: A method for registering digital renal perfusion images includes selecting a volume of interest (VOI) containing a kidney in a reference renal perfusion image, computing 3D intensity gradients for a plurality of points in the VOI of the reference renal perfusion image, computing 3D intensity gradients for a plurality of points in a search window of a current renal perfusion image, and maximizing a similarity measure between the reference image VOI and the current image search window, where the similarity measure is a function of the 3D intensity gradients computed for the reference image and the current image.

Abstract: A method for tracking a contour in cardiac phase contrast flow magnetic resonance (MR) images includes estimating a global translation of a contour in a reference image in a time sequence of cardiac phase contrast flow MR images to a contour in a current image in the time sequence of images by finding a 2-dimensional translation vector that maximizes a similarity function of the contour in the reference image and the current image calculated over a bounding rectangle containing the contour in the reference image, estimating an affine transformation of the contour in the reference image to the contour in the current image, and performing a constrained local deformation of the contour in the current image.

Abstract: A method and related system for automatically and efficiently isolating the heart in Computer Tomography (CT) or Magnetic Resonance Imaging cardiac scans is disclosed. The method involves segmenting a heart within a set of volumetric data. In accordance with one aspect of the present invention, the set of volumetric data is processed to determine the minimum value of an energy function having a first term, a second term and a third term. The heart is segmented based on the processing of the set of volumetric data.

Abstract: A method for segmenting a sequence of images includes developing an autoregressive model using training data including segmented images of a same type as the sequence of images. The sequence of images showing a progression of a subject through a cycle is acquired. At least two images from the sequence of images are identified. A region of interest is manually segmented from the identified images. The manually segmented images are parameterized. The autoregressive model is adapted to the parameterized segmented images. The autoregressive model is used to perform segmentation on the region of interest for a plurality of images of the sequence of images.

Abstract: A method for automatically analyzing an aortic aneurysm includes providing a digitized 3-dimensional image volume of an aorta, determining which voxels in said image are likely to be lumen voxels, determining a distance of said lumen voxels from an aortic boundary, finding a centerline of the aorta in said image volume based on said lumen voxel distances, constructing a series of 2-dimensional multiplanar reformatted (MFR) image planes orthogonal to this centerline, segmenting aortic cross sections in each said MPR image plane wherein an aortic wall is located in each MPR image, and constructing from said aortic wall locations a 3D model of the aorta.

Abstract: Presegmentation or prior, pre-existing segmentation of an object obtained through other means will be presented for interactive editing of a segmented object in an image or volume. Prior segmentation will be seamlessly combined with graph cuts or the random walker methods. Editing of the presegmentation is possible, while maintaining the important property of both methods that an arbitrary segmentation may be achieved with enough interaction.

Abstract: Motion of the heart during contrast enhancement is modeled at two hierarchical levels: global translation and local deformation. Large-scale, i.e., global, translational motion is identified using global template matching, while the local deformation of a portion of the object (e.g., the left ventricle where the object is a heart) is obtained using an adaptive local template matching scheme which adapts to the local edge distributions by varying the height and the width of the template as well as the location of the template followed by spatial regularization. To address the difficulty of rapid intensity changes across the image sequence as the contrast agent perfuse into the tissue, an edge-based similarity measure is used for template matching.

Abstract: A system and method for automatically determining the standard cardiac image views as defined by the American Heart Association from volumetric data of the chest including the heart. The system and method can be used by a health practitioner to quickly see the two dimensional views from which a diagnosis is generally made. The left ventricle is detected. Then the relative orientation of the right ventricle is determined and the standard cardiac views are determined.

Abstract: A method and related system for automatically and efficiently isolating the heart in Computer Tomography (CT) or Magnetic Resonance Imaging cardiac scans is disclosed. The method involves segmenting a heart within a set of volumetric data. In accordance with one aspect of the present invention, the set of volumetric data is processed to determine the minimum value of an energy function having a first term, a second term and a third term. The heart is segmented based on the processing of the set of volumetric data.

Abstract: A system and method for integrated image registration of cardiac magnetic resonance perfusion data are provided, where the system includes an estimation unit for estimating an edge parameter, a registration unit in signal communication with the estimation unit for registering the edge parameter in correspondence with a template-match between pixels in a first input image and pixels in a second input image, and a CPU in signal communication with said estimation unit and said registration unit for detecting a changed pixel location in accordance with said registration when the entropy of said second image is increased; and where the corresponding method for integrated image registration is of cardiac magnetic resonance perfusion data includes providing a contoured region of interest on a first image having a plurality of pixels, receiving a second image corresponding to a time other than that of said first image, calculating pixel intensities for the second image, estimating edge parameters for at least one of

Abstract: A system and method for integrated image registration of cardiac magnetic resonance perfusion data are provided, where the system includes an estimation unit for estimating an edge parameter, a registration unit in signal communication with the estimation unit for registering the edge parameter in correspondence with a template-match between pixels in a first input image and pixels in a second input image, and a CPU in signal communication with said estimation unit and said registration unit for detecting a changed pixel location in accordance with said registration when the entropy of said second image is increased; and where the corresponding method for integrated image registration is of cardiac magnetic resonance perfusion data includes providing a contoured region of interest on a first image having a plurality of pixels, receiving a second image corresponding to a time other than that of said first image, calculating pixel intensities for the second image, estimating edge parameters for at least one of