Algotec Systems Ltd.

Verint Americas Inc.

Carestream Health, Inc.

Verint Systems, Inc.

Shmuel Akerman

Gad Miller

Ido Milstein

Gadi Zimerman

Hadar Porat

Amir Sole

Itsik Horovitz

Itshak Horovitz

Laurent Cohen

Reuven R Shreiber

Michael Slutsky

Hadas H Padan

Gad G Miller

Ido I Milstein

Models are generated from objects identified in video. Each model is evaluated based on knowledge of the objects determined from video analysis, and preferred models are identified based on the evaluations. In some examples, each model could be evaluated by tracking a movement of each object in the video by using each model to track the object from which it was generated, evaluating an ability of each model to identify the objects in the video that are similar to the object from which it was generated, and determining an amount of false identifications made by each model of different objects in different video that does not include the object from which it was generated.

Evaluation of models generated from objects in video

A method for a rapid automated presentation of at least two radiological data sets of a patient, comprising, (a) automatically registering the data sets in 3D space; and (b) concurrently presenting substantially matching anatomical regions in each data set.

Comparison workflow automation by registration

An image analysis system comprising: (a) an image input module adapted to receive a medical image; and (b) an analytic module adapted to segment the image, identify a plurality of vertebrae and label each vertebra.

Spine labeling

A method of centerline determination for a tubular tissue in a medical image data set defined in a data space, comprising receiving at least one start point and one end point inside a tubular tissue volume; automatically determining a path between said points that remains inside said volume; automatically segmenting said tubular tissue using said path; and automatically determining a centerline for said tubular tissue from said segmentation, wherein said receiving, said determining a path and said segmenting, said determining a centerline are all performed on a same data space of said medical image data set.

Vessel centerline determination

A method of finding a path from a start point to a target point, in multi-dimensional space, including: (a) determining a plurality of points in a physical space, including a start point and an target point; (b) computing, using a cost function, for said points an accumulated path cost from the start point to a point; representing a minimal cost path from the start point to the point with respect to an optimization criteria; (c) computing for at least some of said points an estimated-cost-to-target from a point to the target point; and (d) after computing said costs, determining at least one of a minimal path or a minimal path cost of a path from the start point to the target point in the physical space, wherein the determination is based on said accumulated path costs, and is minimal with respect to the optimization criteria.

Targeted marching

A method of automatically identifying bone components in a medical image data set of voxels, the method comprising: a) applying a first set of one or more tests to accept voxels as belonging to seeds, b) applying a second set of one or more tests to accept seeds as bone seeds, and c) expanding the bone seeds into bone components by progressively identifying candidate bone voxels, adjacent to the bone seeds or to other previously identified bone voxels, as bone voxels, responsive to predetermined criteria which distinguish bone voxels from voxels of other body tissue.

Bone segmentation

A method of automatically identifying bone components in a medical image data set of voxels, the method comprising:

A method and system for detecting a boundary between a first tissue and a second tissue in a two-dimensional image. A cost is assigned to each pixel in a detection region indicative of the likelihood that the pixel is not located on the boundary between the first tissue and the second tissue. The boundary between the first and second tissues or organs is a path of voxels of minimal cost in the detection region from among two or more paths, the cost of a path being obtained in a calculation based upon the costs assigned to the voxels of the path. The method may be used to detect a boundary between a first tissue or organ and a second tissue or organ in a three-dimensional scan by applying the method to each of one or more two-dimensional sections and joining the two dimensional boundaries into a three dimensional boundary in the three dimensional scan. The method may also be used in segmenting a three-dimensional body scan.

Method and system for processing an image of body tissues

A method for forming a high spatial resolution perspective rendering from a low spatial resolution voxel space is disclosed. The method comprises steps of: a) initializing a virtual window of predetermined resolution pixels, and placing the virtual window in or near the voxel space; b) sparsely ray-casting a plurality of vectors from a predetermined vantage-point through the virtual window into the voxel space; and c) calculating a visualization-value at a series of positions along each vector. In a position ordering of steps from the vantage-point to the pixel, an accumulated transparency-value threshold is calculated. Values of proximate voxels are interpolated into an interpolated voxel value for each position. The interpolated voxel values are then transformed into a derived visualization-value and transparency value.

Method of forming a perspective rendering from a voxel space

A method of determining a z-buffer for a voxel data set, comprising first raycasting at least a first ray to determine a value for a first z-buffer element; and second raycasting at least a second ray to determine a value for a second z-buffer element, where said z-buffer element values are determined at different accuracies, which different accuracies are responsive to characteristics of the data set at a neighborhood of said rays. Preferably, said different accuracies are achieved by modifying the accuracy of determination of an intersection between a cast ray and a solid voxel of said data set. Alternatively or additionally, said different accuracies are achieved by modifying the density of raycasting into the z-buffer.

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Binyamina, Israel

Shmuel Akerman