Segmentation of 3D medical structures using robust ray...

Computer graphics processing and selective visual display system – Computer graphics processing – Three-dimension

Reexamination Certificate

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C345S419000, C345S426000, C345S427000, C345S581000, C345S583000, C345S589000, C345S621000, C382S128000, C382S173000

Reexamination Certificate

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07015907

ABSTRACT:
A method for segmentation of 3D structures in CT and MR images is provided. The method is based on 3D ray propagation by mean-shift analysis with a smoothness constraint. Ray propagation is used to guide an evolving surface due to its computational efficiency and shape priors are incorporated for robust convergence. The method includes the steps of receiving 3D image data; visualizing the 3D image data on a display device; selecting a structure in the 3D image data by placing a seed in the structure; initializing a plurality of rays from the seed to form a surface; determining a speed function of each of the rays; evolving the surface by propagating the rays based on the speed function of each of the rays; converging the rays on a boundary of the structure; and segmenting the structure when all of the rays have converged on the structure's boundary.

REFERENCES:
patent: 6385332 (2002-05-01), Zahalka et al.
patent: 6785409 (2004-08-01), Suri
patent: 1030187 (2000-08-01), None
Comaniciu et al. “Mean Shift Analysis and Application”, IEEE published Sep. 20-27, 1999, pp. 1-8.
Lakare S et al: “3D digital cleansing using segmentation rays” Proceedings Visualization 2000. VIS 2000 (Cat. No. 00CH37145), Salt Lake City, UT, USA, Oct. 8-13, 2000, pp. 37-44, 538, XP002271797 2000, Piscataway, NJ USA, IEEE, USA sections 3 and 6 abstract.
Tek H et al: “Vessel detection by mean shift based ray propagation” Workshop on Mathematical Methods in Biomedical Image Analysis, Kauai, Hi, USA, Dec. 9-10, 2001. pp. 228-235, XP002271798 2001, Los Alamitos, CA, USA IEEE Comput. Soc, USA ISBN: 0-7695-1336-0 the whole document.
Dorin Comanici and Peter Meer, “Mean Shift: a Robust Approach Toward Feature Space Analysis” IEEE Transactions On Pattern Analysis and Machine Intelligence, vol. 24., No. 5., May 2002, pp. 1-18.

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