DCS-ST for Classification of Breast Cancer Histopathology Images with Limited Annotations

TL;DR

This paper proposes a deep learning approach called DCS-ST to improve breast cancer histopathology image classification when annotations are limited, addressing a key challenge in medical image analysis.

Contribution

The paper introduces DCS-ST, a novel method that enhances classification accuracy with limited annotations in breast cancer histopathology images.

Findings

DCS-ST outperforms existing methods with limited data

Significant improvement in classification accuracy

Effective with fewer annotated samples

Abstract

Deep learning methods have shown promise in classifying breast cancer histopathology images, but their performance often declines with limited annotated data, a critical challenge in medical imaging due to the high cost and expertise required for annotations.