Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …

The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …

The clinical application of breast ultrasound for the assessment of cancer risk and of deep
learning for the classification of breast-ultrasound images has been hindered by inter-grader …

Breast cancer is a major research area in the medical image analysis field; it is a dangerous
disease and a major cause of death among women. Early and accurate diagnosis of breast …

Currently, the automatic segmentation of breast tumors based on breast ultrasound (BUS)
images is still a challenging task. Most lesion segmentation methods are implemented …

Abstract Background and Objective Deep learning detection and classification from medical
imagery are key components for computer-aided diagnosis (CAD) systems to efficiently …

Background Deep learning (DL) is the fastest-growing field of machine learning (ML). Deep
convolutional neural networks (DCNN) are currently the main tool used for image analysis …

A computer-aided diagnosis (CAD) system requires detection, segmentation, and
classification in one framework to assist radiologists efficiently in an accurate diagnosis. In …

Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …