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Breast Cancer Histology Image Classification (20% labels)
3260 papers • 126 benchmarks • 313 datasets
Model's breast cancer histology image classification performance on BreakHis dataset with limited training data labels of 20%.
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BreakHis
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Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
Rajkumar Saini, G. Pihlgren, M. Liwicki, Prakash Chandra Chhipa, Richa Upadhyay, Seiichi Uchida•Mon Mar 14 2022
The proposed method, Magnification Prior Contrastive Similarity (MPCS), enables self-supervised learning of representations without labels on small-scale breast cancer dataset BreakHis by exploiting magnification factor, inductive transfer, and reducing human prior.
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