MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appe...

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Bibliographic Details
Main Authors:	Guo, Yanrong, Zhan, Yiqiang, Gao, Yaozong, Jiang, Jianguo, Shen, Dinggang
Format:	Artigo
Language:	Inglês
Published:	2013
Subjects:	Article
Online Access:	https://ncbi.nlm.nih.gov/pmc/articles/PMC4097123/ https://ncbi.nlm.nih.gov/pubmed/25035792 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI.2013.6556613
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MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING

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