Screening for breast cancer with mammography has been introduced in various countries
over the last 30 years, initially using analog screen-film-based systems and, over the last 20 …

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 imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

Purpose To compare breast cancer detection performance of radiologists reading
mammographic examinations unaided versus supported by an artificial intelligence (AI) …

The rapid development of deep learning, a family of machine learning techniques, has
spurred much interest in its application to medical imaging problems. Here, we develop a …

We present a deep convolutional neural network for breast cancer screening exam
classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our …

This article reviews current limitations and future opportunities for the application of
computer-aided detection (CAD) systems and artificial intelligence in breast imaging …

This work delivers a novel technique to detect brain tumor with the help of enhanced
watershed modeling integrated with a modified ResNet50 architecture. It also involves …

Medical images differ from natural images in significantly higher resolutions and smaller
regions of interest. Because of these differences, neural network architectures that work well …

The heavy global burden and mortality of breast cancer emphasize the importance of early
diagnosis and treatment. Imaging detection is one of the main tools used in clinical practice …