Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach.
Journal:
Diagnostic and interventional radiology (Ankara, Turkey)
Published Date:
Dec 9, 2024
Abstract
PURPOSE: The purpose of this study was to propose a new computer-assisted two-staged diagnosis system that combines a modified deep learning (DL) architecture (VGG19) for the classification of digital breast tomosynthesis (DBT) images with the detection of tumors as benign or cancerous using the You Only Look Once version 5 (YOLOv5) model combined with the convolutional block attention module (CBAM) (known as YOLOv5-CBAM).