DCS-ST for Classification of Breast Cancer Histopathology Images with Limited Annotations
This work tackles the problem of data scarcity in medical image analysis for breast cancer diagnosis, which is incremental as it builds on existing deep learning approaches to handle limited annotations.
The paper addresses the challenge of classifying breast cancer histopathology images when only limited annotated data is available, which is a critical issue in medical imaging due to high annotation costs and expertise requirements, and it proposes a method to improve performance under these constraints.
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.