The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Although computer-aided diagnosis (CAD) is widely used in mammography, conventional
CAD programs that use prompts to indicate potential cancers on the mammograms have not …

Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …

This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …

Background Improved breast cancer risk assessment models are needed to enable
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …

Computer-aided diagnosis (CAD) has been a popular area of research and development in
the past few decades. In CAD, machine learning methods and multidisciplinary knowledge …

Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally.
Breast cancer detection needs accurate mammography interpretation and analysis, which is …

This study reviews the technique of convolutional neural network (CNN) applied in a specific
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …

During the past decade, researchers have investigated the use of computer-aided
mammography interpretation. With the application of deep learning technology, artificial …

Breast density estimation with visual evaluation is still challenging due to low contrast and
significant fluctuations in the mammograms' fatty tissue background. The primary key to …