Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification-Reference-Cited by-同舟云学术

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification

Published:2021-10 Issue: Volume:73 Page:102165
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Marini Niccolò,Otálora Sebastian,Müller Henning,Atzori Manfredo

Funder

Horizon 2020

Horizon 2020 Framework Programme

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference62 articles.

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4. Prostate needle biopsies: interobserver variation and clinical consequences of histopathological re-evaluation;Berg;APMIS,2011

5. Automated deep-learning system for gleason grading of prostate cancer using biopsies: a diagnostic study;Bulten;Lancet Oncol.,2020

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