Inventors:
Parmeshwar Khurd - Princeton NJ, US
Leo Grady - Yardley PA, US
Ali Kamen - Skillman NJ, US
Mamadou Diallo - Plainsboro NJ, US
Kalpitkumar Gajera - Mountain View CA, US
Peter Gall - Buckenhof, DE
Martin Requardt - Nurnberg, DE
Berthold Kiefer - Erlangen, DE
Clifford R. Weiss - Baltimore MD, US
Assignee:
Siemens Corporation - Iselin NJ
International Classification:
G06K 9/34, G06K 9/62
Abstract:
Automatic prostate localization in T2-weighted MR images facilitate labor-intensive cancer imaging techniques. Methods and systems to accurately segment the prostate gland in MR images are provided and address large variations in prostate anatomy and disease, intensity inhomogeneities, and artifacts induced by endorectal coils. A center of the prostate is automatically detected with a boosted classifier trained on intensity based multi-level Gaussian Mixture Model Expectation Maximization (GMM-EM) segmentations of the raw MR images. A shape model is used in conjunction with Multi-Label Random Walker (MLRW) to constrain the seeding process within MLRW.