1 Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China 2 Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou ...
Abstract: Accurate and early breast cancer detection is critical for improving patient outcomes. In this study, we propose PatchCascade-ViT, a novel self-supervised Vision Transformer (ViT) framework ...
Abstract: Breast cancer remains one of the most prevalent cancers among women worldwide, underscoring the critical need for early and accurate detection methods. The Breast Imaging Reporting and Data ...
This project implements deep learning models to classify mammogram images into BI-RADS categories using the King Abdulaziz University Medical Dataset (KAUMDS). We explore both custom and pretrained ...
Objective: In this study, we aimed to explore the diagnostic value of a deep learning (DL) model based on mammography for Breast Imaging Reporting and Data System (BI-RADS) 4 lesions and to reduce ...
Mammography remains the most prevalent imaging tool for early breast cancer screening. The language used to describe abnormalities in mammographic reports is based on the Breast Imaging Reporting and ...
The BI-RADS mammographic classification system begins with the indication for the study. The patient history is included in this section. The mammographer must also describe whether the study is a ...