Accurate segmentation of prostate cancer histomorphometric features using a weakly supervised convolutional neural network

Purpose: Prostate cancer primarily arises from the glandular epithelium. Histomophometric techniques have been used to assess the glandular epithelium in automated detection and classification pipelines; however, they are often rigid in their implementation, and their performance suffers on large da...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:J Med Imaging (Bellingham)
मुख्य लेखकों: Bukowy, John D., Foss, Halle, McGarry, Sean D., Lowman, Allison K., Hurrell, Sarah L., Iczkowski, Kenneth A., Banerjee, Anjishnu, Bobholz, Samuel A., Barrington, Alexander, Dayton, Alex, Unteriner, Jackson, Jacobsohn, Kenneth, See, William A., Nevalainen, Marja T., Nencka, Andrew S., Ethridge, Tyler, Jarrard, David F., LaViolette, Peter S.
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: Society of Photo-Optical Instrumentation Engineers 2020
विषय:
Digital Pathology
ऑनलाइन पहुंच:https://ncbi.nlm.nih.gov/pmc/articles/PMC7550797/
https://ncbi.nlm.nih.gov/pubmed/33062803
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.5.057501
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