Atlas Based AAM and SVM Model for Fully Automatic MRI Prostate Segmentation

Automatic prostate segmentation in MR images is a challenging task due to inter-patient prostate shape and texture variability, and the lack of a clear prostate boundary. We propose a supervised learning framework that combines the atlas based AAM and SVM model to achieve a relatively high segmentat...

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Bibliografiske detaljer
Udgivet i:Conf Proc IEEE Eng Med Biol Soc
Main Authors: Cheng, Ruida, Turkbey, Baris, Gandler, William, Agarwal, Harsh K., Shah, Vijay P., Bokinsky, Alexandra, McCreedy, Evan, Wang, Shijun, Sankineni, Sandeep, Bernardo, Marcelino, Pohida, Thomas, Choyke, Peter, McAuliffe, Matthew J.
Format: Artigo
Sprog:Inglês
Udgivet: 2014
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Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6748308/
https://ncbi.nlm.nih.gov/pubmed/25570593
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/EMBC.2014.6944225
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