Abstract: Method and system for multiple volume exploration is disclosed. A first 3D volume is rendered in a first region. One or representations are displayed in a second region, where each representation signifies a stack of 2D images. A first stack represents one or more 2D images of cross sections of a certain orientation from the first 3D volume. Each of the other stacks includes one or more 2D images of cross sections of the same orientation from a 3D volume related to the first 3D volume.

Abstract: A method and system is provided for data/process sharing. A decapsulating unit is provided and resides on first system where a first application system resides. The decapsulating unit monitors, on the first system, when encapsulated data from a second application system residing on a second system, is present in the first application system. The encapsulated data, once present on the first system, is decapsulated by the decapsulating unit to obtain a trigger corresponding to the second application system and encapsulated in the encapsulated data. The obtained trigger is analyzed and the second application system is launched on the first system based on the trigger.

Abstract: A method and system provided for interactive liver data processing. A vessel system with a plurality of vessel branches is obtained. Centerlines for the vessel branches are extracted and used to construct a graph representation of the vessel system. Each vessel branch in the vessel system can be labeled based on the graphic representation.

Abstract: Method and system for multiple volume exploration is disclosed. A first 3D volume is rendered in a first region. One or representations are displayed in a second region, where each representation signifies a stack of 2D images. A first stack represents one or more 2D images of cross sections of a certain orientation from the first 3D volume. Each of the other stacks includes one or more 2D images of cross sections of the same orientation from a 3D volume related to the first 3D volume.

Abstract: Method and system for 3D data editing is disclosed. A 3D volumetric data is rendered in a rendering space. A 2D graphical drawing tool is selected and used to create a 2D structure. Apply a 3D operation to the 3D volumetric data based on the 2D structure.

Abstract: An algorithm is disclosed that recovers regions of possible pleural nodules left out of an organ field or otherwise undetected due to the nature of low level image processing in the organ field. A morphological closing with an elliptical structuring element is performed on a region to detect nodules within the size of the ellipsoid. A deformable surface-based analysis is performed in distinctive regions for the identification of larger nodules. The integrated use of a deformable surface model and chamfer distance potential enables explicit representation of regularized, or smoothed, surfaces within which nodule candidates may be detected.

Abstract: An algorithm is disclosed that detects and analyzes possible lesions that are left in contact with a structural boundary. A morphological closing with a structuring element is performed along the boundary to detect lesions within the threshold of the structuring element. A deformable surface-based analysis is performed on distinctive surfaces of the structure for the identification of lesions. The integrated use of a deformable surface model and chamfer distance potential enables explicit representation of regularized, or smoothed, surfaces from which lesion candidates may be detected.

Abstract: A method and system of volume segmentation is disclosed. To address throughput and accuracy issues, the segmentation is divided into two stages: presegmentation and detailed segmentation. In presegmentation, a digital image volume is segmented into different anatomical structures. In the detailed segmentation, additional processing over a limited range is performed. The result of the volume segmentation is a volume in which segmented regions of interest, such as nodules, are labeled or identified.

Abstract: A method and system of volume segmentation is disclosed. To address throughput speed and accuracy requirements, the segmentation is divided into two stages: presegmentation and detailed segmentation. In presegmentation, a digital image volume is processed to identify anatomical structures from image backgrounds in a gross manner possibly at reduced image resolution. Detailed segmentation then involves refining and segmenting further the fine details within the anatomical structures identified by presegmentation. One result of the overall volume segmentation algorithm is a volume in which segmented regions of interest, such as nodules, are identified.

Abstract: An algorithm is disclosed that recovers regions of possible pleural nodules left out of an organ field or otherwise undetected due to the nature of low level image processing in the organ field. A morphological closing with an elliptical structuring element is performed on a region to detect nodules within the size of the ellipsoid. A deformable surface-based analysis is performed in distinctive regions for the identification of larger nodules. The integrated use of a deformable surface model and chamfer distance potential enables explicit representation of regularized, or smoothed, surfaces within which nodule candidates may be detected.