Vital Images, Inc.

Marek Brejl

Samuel W Peterson

Annapoorani Gothandaraman

Todd L Johnson

Vincent J Argiro

Renee Maheshwari Rashid

Marguerite Kirkby

Milan Brejl

Thomas J Gleeson

Zhujiang Cao

A method including searching image data corresponding to a series of axial image slices with a processor, searching axial image slices from a starting image slice and calculating a confidence score that an image slice includes a cross-section image of an aorta, identifying an image slice containing at least one seed disk, including an ascending aorta seed disk, from candidate image slices identified according to the confidence score, and growing a 3D segmentation of the ascending aorta by stacking ascending aorta image disks included in consecutive image slices beginning from the ascending aorta seed disk.

Automatic aortic detection and segmentation in three-dimensional image data

A method of operating on volumetric imaging data representing organ anatomy includes determining whether a polyp location within a specified range from a viewing point is visible, or hidden by an anatomical feature, and marking the polyp as visible or hidden with a viewable indicator.

Systems and methods for virtual identification of polyps

This document discusses, among other things, systems and methods for efficiently calculating a colon segmentation from one or more candidate virtual three-dimensional objects. A sequence of image scans are analyzed and candidate segments are identified. Landmark segments are identified from the candidate segments. A characteristic path is generated for each candidate segment. The paths are joined using a cost network and reoriented to be consistent with a typical flythrough path. The connected path is then used to generate a continuous volumetric virtual object.

Characteristic path-based colon segmentation

This document discusses, among other things, systems and methods for efficiently calculating a registration of multiple characteristic paths of a virtual three-dimensional object. Each path of discrete points is transformed into a piecewise linear parameterization as a function of path length. The paths are smoothed and normalized. The shorter path is partitioned into a number of discrete subintervals. The subintervals are mapped to the longer path using a minimization function that minimizes a cost function resulting in a locally optimal registration. The shorter path is incrementally positioned along the longer path and the minimization is attempted at each position. When the shorter path cannot be shifted any farther, the globally optimal registration is returned.

Colon characteristic path registration

This document discusses, among other things, systems and methods for efficiently calculating a colon segmentation from one or more candidate virtual three-dimensional objects. A sequence of image scans are analyzed and regions that represent air-filled objects and tagged-stool are identified as candidate segments. A characteristic path is generated for each candidate segment. The paths are joined using a cost network and re-oriented to be consistent with a typical flythrough path. The connected path is then used to generate a continuous volumetric virtual object.

Systems and methods for deriving a cardiac cycle signal by selecting images of a portion of a cardiovascular system include receiving a plurality of images from a scanner that have been recorded over a period of time. The images represent one or more locations along the extent of the cardiovascular system. The images are then selected based on common criteria determined from the plurality of images and without reference to an external signal. The common criteria comprises changes in the size of a cross section of the aorta, changes in the volume of the heart, changes in the area of a cross section of the heart. In addition, the criteria can include the mean pixel difference between adjacent images.

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Eden Praire, MN, United States of America

Marek Brejl