This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …

Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …

Background With the development of digital pathology and the renewal of deep learning
algorithm, artificial intelligence (AI) is widely applied in tumor pathology. Previous …

Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

[37] OI Khalaf, GM Abdulsahib and BM Sabbar,“Optimization of wireless sensor network
coverage using the bee algorithm,” Journal of Information Science and Engineering, vol. 36 …

Low-light image enhancement (LLIE) is a common pretext task for computer vision, which
aims to adjust the luminance of the low-light image to obtain the normal-light image. At …

Background of the study Breast cancer is the most fatal disease that widely affects women.
When the cancerous lumps grow from the cells of the breast, it causes breast cancer. Self …

There is great interest in the development of artificial intelligence (AI) applications for
medical imaging in general and specifically in breast imaging. Because of the scale of …

Purpose The aim of this study is to perform a test object‐based comparison of the imaging
performance of digital mammography (DM), digital breast tomosynthesis (DBT), and …

In this study, we evaluated the improvement of image quality in digital breast tomosynthesis
under low-radiation dose conditions of pre-reconstruction processing using conditional …