Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections

Accurate and automated prostate whole gland and central gland segmentations on MR images are essential for aiding any prostate cancer diagnosis system. Our work presents a 2-D orthogonal deep learning method to automatically segment the whole prostate and central gland from T2-weighted axial-only MR...

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Detalhes bibliográficos
Publicado no:J Med Imaging (Bellingham)
Main Authors: Cheng, Ruida, Lay, Nathan, Roth, Holger R., Turkbey, Baris, Jin, Dakai, Gandler, William, McCreedy, Evan S., Pohida, Tom, Pinto, Peter, Choyke, Peter, McAuliffe, Matthew J., Summers, Ronald M.
Formato: Artigo
Idioma:Inglês
Publicado em: Society of Photo-Optical Instrumentation Engineers 2019
Assuntos:
Image Processing
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6551111/
https://ncbi.nlm.nih.gov/pubmed/31205977
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.6.2.024007
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