System and method for volumetric tumor segmentation using...

Image analysis – Image segmentation

Reexamination Certificate

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C382S128000, C382S190000, C382S199000, C382S274000

Reexamination Certificate

active

07430321

ABSTRACT:
A method for segmenting a digitized image includes providing a digitized volumetric image comprising a plurality of intensities corresponding to a domain of points in an N-dimensional space, identifying a target structure in said image, forming a window about said target structure whose size is a function of the target scale, and performing a joint space-intensity-likelihood ratio test at each point within said window to determine whether each said point is within said target structure.

REFERENCES:
patent: 2004/0013292 (2004-01-01), Raunig
patent: 2004/0022438 (2004-02-01), Hibbard
patent: 2004/0253649 (2004-12-01), Smith
patent: 2005/0170528 (2005-08-01), West et al.
patent: 2007/0185656 (2007-08-01), Schadt
patent: 2008/0002873 (2008-01-01), Reeves et al.
Okada, Kazunori et al. “Scale Selection for Anisotropic Scale-Space: Application to volumetric Tumor Characterization,”Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,vol. 1, Jun. 27, 2004 pp. 594-601 XP010708815 Abstract.
Dugas-Phocion G. et al., “Hierarchical segmentation of multiple sclerosis lesions in multi-sequence MRI,”Biomedical Imaging: Macro to Nano, 2004 IEEE International Symposium on Arlington, VA,Apr. 15-18 pp. 157-160; XP010773821 Abstract.
Okada K et al., “Robust 3D segmentation of Pulmonary Nodules in Multislice CT Images,”Lecture Notes in Computer Science,Sep. 26, 2004 vol. 3217, pp. 881-889 XP008047180 Abstract.
Okada K et al., “Blog Segmentation Using Joint Space-Intensity Likelihood Ratio Test: Application to 3D Tumor Segmentation,”Computer Vision and Pattern Recognition,Jun. 20, 2005, pp. 437-444, XP010817630 Abstract.
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