High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolut...
High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection
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United States: Public Library of Science
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Language
English
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United States: Public Library of Science
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Contents
Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detecti...
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High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection
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TN_cdi_plos_journals_2043737792
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2043737792
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0196828
