Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks

Accurate automatic segmentation of the prostate in magnetic resonance images (MRI) is a challenging task due to the high variability of prostate anatomic structure. Artifacts such as noise and similar signal intensity of tissues around the prostate boundary inhibit traditional segmentation methods f...

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Veröffentlicht in:J Med Imaging (Bellingham)
Hauptverfasser: Cheng, Ruida, Roth, Holger R., Lay, Nathan, Lu, Le, Turkbey, Baris, Gandler, William, McCreedy, Evan S., Pohida, Tom, Pinto, Peter A., Choyke, Peter, McAuliffe, Matthew J., Summers, Ronald M.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Society of Photo-Optical Instrumentation Engineers 2017
Schlagworte:
Special Section on Radiomics and Deep Learning
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC5565676/
https://ncbi.nlm.nih.gov/pubmed/28840173
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.4.4.041302
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