Papers › Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

2 Feb 2018arXiv:1802.00752archive 2025-07-28

Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov, Alexandr A. Kalinin

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Hematoxylin and eosin stained breast histology microscopy image dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our approach utilizes several deep neural network architectures and gradient boosted trees classifier. For 4-class classification task, we report 87.2% accuracy. For 2-class classification task to detect carcinomas we report 93.8% accuracy, AUC 97.3%, and sensitivity/specificity 96.5/88.0% at the high-sensitivity operating point. To our knowledge, this approach outperforms other common methods in automated histopathological image classification. The source code for our approach is made publicly available at https://github.com/alexander-rakhlin/ICIAR2018

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1ran · our draft was wrong
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combine_model_scores alexander-rakhlin/ICIAR2018/crossvalidate_blending.py official repository ran · fixture could not drive it fingerprinted MIT (permissive) · 55528ffe915a2cb1 · report
hematoxylin_eosin_aug vavaidya/breast-cancer-detection/ICIAR2018/feature_extractor.py community (archive-listed) ran · fixture could not drive it fingerprinted no licence file found · pointer only · 21cfedf3ffb6fdaa · report
normalize_staining vavaidya/breast-cancer-detection/ICIAR2018/feature_extractor.py community (archive-listed) ran · fixture could not drive it fingerprinted no licence file found · pointer only · 4c7a8277f6a50e09 · report
recursive_glob vavaidya/breast-cancer-detection/ICIAR2018/feature_extractor.py community (archive-listed) ran · our draft was wrong no licence file found · pointer only · aa04f8cb7595031f · report

Tasks

Breast Cancer DetectionBreast Cancer Histology Image ClassificationClassificationDiagnosticGeneral ClassificationHistopathological Image ClassificationImage ClassificationMedical Image AnalysisSensitivitySpecificityimage-classification

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Methods

Convolution

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