Abstract: A system and method for toboggan-based object detection in cutting planes are provided. A method for detecting an object in an image includes: determining a region of interest (ROI) in the image; determining a toboggan potential for each image element in the ROI; extracting a plurality of cutting planes from the ROI; and performing a tobogganing in the cutting planes to form a toboggan cluster to determine a location of the object, wherein image elements inside the toboggan cluster are stored in a cluster-member list, image elements on an outer-border of the toboggan cluster are stored in an outer-border list and image elements on an inner-border of the toboggan cluster are stored in an inner-border list.

Abstract: An exemplary method of detecting one or more objects in image data is provided. The image data includes a plurality of pixels/voxels. The method includes sliding pixels/voxels that meet sliding criteria; and collecting the slid pixels/voxels that satisfy collecting criteria. An exemplary method of segmenting an object in image data is also provided. The method includes receiving an initial pixel/voxel in the image data; and forming a segmentation of the object based on the initial pixel/voxel.

Abstract: Motion is automatically characterized from ultrasound information. Ultrasound information associated with particular time periods relative to a cycle, such as the cardiac cycle, are extracted, such as identifying and extracting ultrasound information associated with systole. By tracking an area of the heart, such as an area within the endocardial contour, the heart cycle time periods are identified. Spatial parameter values are determined as a function of time from the extracted ultrasound information. For example, the timing of motion, the eigen motion, the curvature, the local ejection-fraction ratio and/or the bending energy of parts of the cardiac tissue are determined. The spatial parameter values characterize the motion.

Abstract: A method for characterizing an object in a digitized image includes providing a digitized volumetric image comprising a plurality of intensities corresponding to a domain of points in an N-dimensional space, forming a toboggan cluster from a subset of contiguous points in said image, said toboggan cluster including a concentration point, extracting a first layer from said toboggan cluster, and computing one or more features from said toboggan layer.

Abstract: A method of segmenting an object in a digital image comprising providing a digital image comprising a plurality of intensities corresponding to a domain of points in a N-dimensional space, selecting a region of interest in the image, determining a threshold intensity value for points in said region of interest, wherein an object of interest is defined by points with an intensity above a first pre-determined threshold, computing a distance map for each point in said object of interest, tobogganing each point in said object of interest based on said distance map, and selecting a cluster based on the results of said tobogganing.

Abstract: A method of identifying an object in a digital image includes finding a point in a digital image that is a concentration location, initializing a cluster with said concentration location, adding the neighboring points of the concentration location to a list, selecting a neighbor point with an extremal potential value from said list, determining a slide direction of all neighbors of said selected point and identifying those neighbors that slide to the selected point, adding those neighbor points not already in the list to the list, adding the selected point to the cluster, and repeating the steps of selecting a neighbor point with an extremal potential value, determining a slide direction, adding points to the list, and adding the selected point to the cluster, until the list is empty.

Abstract: A method and device for segmenting one or more candidates in an image having image elements is disclosed. The method includes identifying a location for one of the candidates in the image, where the location is based at a given image element, and computing one or more response values at neighboring image elements that are in a neighborhood of the location. Image element clusters are created from the computed response values and one or more of the image element clusters are selected as object segmentations for one or more of the candidates.

Abstract: A method and apparatus for characterizing an image. The method selects one or more toboggan potentials from the image, or a portion thereof, to be tobogganed. It toboggans the selected toboggan potentials to generate one or more toboggan parameters, forming at least one toboggan cluster using one or more of the toboggan parameters. It also selects one or more of the toboggan clusters to compute at least one feature parameter to characterize the image or a portion thereof.

Abstract: A system and method for detecting a shape in an image are provided. The method comprises: constructing a deformable model from an image; deforming the deformable model to remove an undesired shape in a portion of the image; computing properties of the deformed model to enable detection of a desired shape in the portion of the image; and detecting the desired shape based on the computed properties.