Wavelet Enhanced Deformable Convolutional Network for Breast Cancer Classification in High Resolution Histopathology Images

Overview

This AI-powered tool is designed to improve the accuracy and accessibility of breast cancer diagnosis, particularly in low-resource settings with limited medical specialists and diagnostic infrastructure. Evaluated on the widely used BreaKHis dataset, it achieved 96.47% accuracy at the image level and 96.55% at the patient level, with especially strong performance on high-magnification (200×) images where fine tissue details are critical for diagnosis. By leveraging advanced AI, the tool supports timely and precise detection, helping healthcare providers deliver better outcomes for patients.

Responsible AI Practices

Its relatively low computational demand, which makes it more feasible for use in hospitals and diagnostic centers that lack high end computing resources or expert personnel.