Artificial intelligence has aided in the advancement of healthcare research. The availability
of open-source healthcare statistics has prompted researchers to create applications that aid …

Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …

Breast lesion detection using ultrasound imaging is considered an important step of
computer-aided diagnosis systems. Over the past decade, researchers have demonstrated …

Breast ultrasound and computer aided diagnosis (CAD) has been used to classify tumors
into benignancy or malignancy. However, conventional CAD software has some problems …

Deep learning methods, especially convolutional neural networks, have been successfully
applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern …

A computer-aided diagnosis (CAD) system based on mammograms enables early breast
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …

This paper proposes a deep convolutional neural network (CNN) model for automated
breast cancer classification from a different class of images, namely, mammograms and …

Breast cancer is one of the most common forms of cancer among women worldwide. The
development of computer-aided diagnosis (CAD) technology based on ultrasound imaging …

Breast cancer is one of the most vulnerable malignant tumors for women in the world, which
seriously threatens women's life and health. Breast ultrasound imaging technology is widely …

Purpose We propose a deep learning‐based approach to breast mass classification in
sonography and compare it with the assessment of four experienced radiologists employing …