Method for Segmenting Medical Images and Detecting Surface Anomalies in Anatomical Structures
Description of Invention:
The invention is a method for automatically detecting surface anomalies in anatomical structures in virtual colonoscopy and other imaging studies. A region growing method segments three-dimensional image data of an anatomical structure using a tortuous path length limit to constrain voxel growth. The path length limit constrains the number of successive generations of voxel growth from a seed point to prevent leakage of voxels outside the boundary of the anatomical structures. Once segmented, a process for detecting surface anomalies performs a curvature analysis on a computer model of the surface of the structure. This process detects surface anomalies automatically by traversing the vertices in the surface model, computing partial derivatives of the surface at the vertices, and computing curvature characteristics from the partial derivatives. To identify possible anomalies, the process compares the curvature characteristics with predetermined curvature characteristics of anomalies and classifies the vertices. The process further refines potential anomalies by segmenting neighboring vertices that are classified as being part of an anomaly using curvature characteristics. Finally, the process colorizes the anomalies, and computes a camera position and direction for each one to assist the user in viewing 2D rendering of the computer model.
The method may be useful for automated detection of inflammatory, pre-cancerous and cancerous lesions of internal body cavities, such as the colon, airways, blood vessels and bladder. An example of a potential commercial application is as a component of software for clinical interpretation of virtual colonoscopy (CT colonography) examinations.
Inventors:
Ronald M. Summers et al. (CC)
Patent Status:
DHHS Reference No. E-040-1997/0 --
U.S. Patent 6,246,784 issued 12 Jun 2001
U.S. Patent 6,345,112 issued 05 Feb 2002
U.S. Patent 6,556,696 issued 29 Apr 2003
Relevant Publication: Summers et al., "Automated Polyp Detection at CT Colonography: Feasibility Assessment in a Human Population," Radiology 219:51-59 (2001)
Summers et al., "Colonic Polyps: Complementary Role of Computer-Aided Detection in CT Colonography," Radiology 225:391-399 (2002)
For Additional Information Please Contact: Michael Shmilovich J.D.
NIH Office of Technology Transfer
6011 Executive Blvd, Suite 325
Rockville, MD 20852-3804
Phone: (301) 435-5019
Email: shmilovm@mail.nih.gov
Fax: (301) 402-0220
