Early detection of breast cancer plays a crucial role in reducing the number of cases diagnosed at advanced stages, thereby lowering the high healthcare costs required to achieve disease-free survival and helping to prevent avoidable premature deaths...
The mortality risk associated with breast cancer is experiencing an exponential rise, underscoring the critical importance of early detection. It is the primary cause of mortality among women under 50 and ranks as the second deadliest disease globall...
Image denoising is a critical problem in low-level computer vision, where the aim is to reconstruct a clean, noise-free image from a noisy input, such as a mammogram image. In recent years, deep learning, particularly convolutional neural networks (C...
The rising global incidence of breast cancer and the persistent shortage of specialized radiologists have heightened the demand for innovative solutions in mammography screening. Artificial intelligence (AI) has emerged as a promising tool to bridge ...
Artificial intelligence (AI) improves the accuracy of mammography screening, but prospective evidence, particularly in a single-read setting, remains limited. This study compares the diagnostic accuracy of breast radiologists with and without AI-base...
Predicting low nuclear grade DCIS before surgery can improve treatment choices and patient care, thereby reducing unnecessary treatment. Due to the high heterogeneity of DCIS and the limitations of biopsies in fully characterizing tumors, current dia...
OBJECTIVE: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for full-field digital mammography (FFDM) when applied to synthetic mammography (SM).
High-attenuation (HA) artifacts may lead to obscured subtle lesions and lesion over-estimation in digital breast tomosynthesis (DBT) imaging. High-attenuation artifact suppression (HAAS) is vital for widespread DBT applications in clinic. The convent...
Purpose To test a commercial artificial intelligence (AI) system for breast cancer detection at the BC Cancer Breast Screening Program. Materials and Methods In this retrospective study of 136 700 female individuals (mean age, 58.8 years ± 9.4 [SD]; ...
IEEE journal of biomedical and health informatics
40030302
Breast cancer is a pervasive global health concern among women. Leveraging multimodal data from enterprise patient databases-including Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHRs)-holds promise for improving...