Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks

Two deep-learning algorithms designed to classify images according to the Gleason grading system that used transfer learning from two well-known general-purpose image classification networks (AlexNet and GoogleNet) were trained on Hematoxylin–Eosin histopathology stained microscopy images with prost...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Rom J Morphol Embryol
المؤلفون الرئيسيون: Şerbănescu, Mircea-Sebastian, Manea, Nicolae Cătălin, Streba, Liliana, Belciug, Smaranda, Pleşea, Iancu Emil, Pirici, Ionica, Bungărdean, Raluca Maria, Pleşea, Răzvan Mihail
التنسيق: Artigo
اللغة:Inglês
منشور في: Academy of Medical Sciences, Romanian Academy Publishing House, Bucharest 2020
الموضوعات:
Original Paper
الوصول للمادة أونلاين:https://ncbi.nlm.nih.gov/pmc/articles/PMC7728132/
https://ncbi.nlm.nih.gov/pubmed/32747906
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.47162/RJME.61.1.17
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