Abstract: 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.

Abstract: 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 re-oriented to be consistent with a typical flythrough path. The connected path is then used to generate a continuous volumetric virtual object.

Abstract: 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.

Abstract: 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.

Abstract: This document discusses, among other things, systems and methods for segmenting and displaying blood vessels or other tubular structures in volumetric imaging data. The vessel of interest is specified by user input, such as by using a single point-and-click of a mouse or using a menu to select the desired vessel. A central vessel axis (CVA) or centerline path is obtained. A segmentation algorithm uses the centerline to propagate a front that collects voxels associated with the vessel. Re-initialization of the algorithm permits control parameter(s) to be adjusted to accommodate local variations at different parts of the vessel. Termination of the front occurs, among other things, upon vessel departure, for example, indicated by a speed of front evolution falling below a predetermined threshold.