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What is FPGA-Enhanced BI-RADS Breast Cancer Classifier about?

This document summarizes a research paper that proposes a real-time breast cancer classification system using deep learning and FPGA techniques. The system uses a custom Digital Mammogram Diagnostic Convolutional Neural Network (DMD-CNN) model trained on BI-RADS data to classify mammogram images into BI-RADS categories. For real-time deployment, the DMD-CNN model is accelerated using an Artix 7 FPGA, allowing it to process over 91 images per second. Experimental results show the proposed system achieves 98.

Author

hajer

Language

EN