Editing of presegemented images/volumes with the multilabel...

Image analysis – Image segmentation

Reexamination Certificate

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C345S619000

Reexamination Certificate

active

07729537

ABSTRACT:
Presegmentation or prior, pre-existing segmentation of an object obtained through other means will be presented for interactive editing of a segmented object in an image or volume. Prior segmentation will be seamlessly combined with graph cuts or the random walker methods. Editing of the presegmentation is possible, while maintaining the important property of both methods that an arbitrary segmentation may be achieved with enough interaction.

REFERENCES:
patent: 2003/0099390 (2003-05-01), Zeng et al.
patent: 2004/0008886 (2004-01-01), Boykov
patent: 2006/0147126 (2006-07-01), Grady
Meila et al. “Learning Segmentation by Random Walks”, MIT Press Advances in Neural Information Processing Systems 13, Dec. 2001, pp. 873-879.
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Boykov et al. “Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images”; Proceedings of International Conference on Computer Vision, Jul. 2001, vol. I pp. 105-112.
Meila et al. “A Random Walks View of Spectral Segmentation”; in AI and Statics (AISTATS) Feb. 14, 2001.
Zheng et al. “Automatic determination of intrinsic cluster number family in spectral clustering using random walk on graph”; International Conference on Image Processing (ICIP) Oct. 2004, vol. 5, pp. 3471-3474.
Freedman D et al: “Interactive Graph Cut Based Segmentation with Shape Priors” Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on San Diego, CA, USA, Jun. 20-26, 2005, Piscataway, NJ, USA, IEEE, Jun. 20, 2005, pp. 755-762, XP010817349 ISBN: 0-7695-2372-2 *abstract*; Others; 2005; US.
Grady L et al: “Multi-label image sementation for medical applications based on graph-theoretic electrical potentials” Lecture Notes in Computer Science, Springer Verlag, Berlin, DE, vol. 3117, 2004, pp. 230-245, XP008084681 ISSN: 0302-9743 *abstract* *sections 2.1 and 2.5*; Others; 2004; DE.
Boykov et al., Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images, Proceedings of International conference on Computer Vision, Jul. 2001.
Cremers et al., Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford'Shah Functional, Kluwer Academic Publishers, 2002.
Elder et al., Image Editing in the Contour Domain, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, No. 3, Mar. 2001.
Falcao et al., User Steered Image Segmentation Paradigms: Live Wire and Live Lane, Graphical Models and Image Processing 60, 233-260, 1998.
Kang et al., Interactive 3D Editing Tools for Image Segmentation, Medical Image Analysis 8, 35-46, 2004.
Lefohn et al., Interactive, GPU—Based Level Sets for 3D Segmentation.
Leventon et al., Statistical Shape Influence in Geodesic Active Contours, Proc. Conf. Computer Vision and Pattern Recognition, vol. 1, Hilton Head Island, SC, Jun. 13-15, 2000, pp. 316-323.
Boykov et al., Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images, Proceedings of International conference on Computer Vision, vol. I, Jul. 2001, pp. 105-112.
Cremers et al., Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford'Shah Functional, International Journal of Computer Vision, vol. 50, No. 3, pp. 295-313, Dec. 2002.
Elder et al., Image Editing in the Contour Domain, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, No. 3, pp. 291-296, Mar. 2001.
Falcao et al., User Steered Image Segmentation Paradigms: Live Wire and Live Lane, Graphical Models and Image Processing 60, pp. 233-260, 1998, (Earlier than this application Aug. 1, 2005).
Kang et al., Interactive 3D Editing Tools for Image Segmentation, Medical Image Analysis 8, pp. 35-46, 2004, (Earlier than this application Aug, 1, 2005).
Lefohn et al., Interactive, GPU—Based Level Sets for 3D Segmentation,MICCAI 2003(2003), pp. 564-572, (Earlier than this application Aug. 1,2005).

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