Some recent studies have described deep convolutional neural networks to diagnose breast
cancer in mammograms with similar or even superior performance to that of human experts …

Breast cancer (BrCa) is the most common disease in women worldwide. Classifying the
BrCa image is extremely important for finding BrCa at an earlier stage and monitoring BrCa …

Abstract X-ray, MRI, and CT scan images etc, are widely used for the detection of various
prevalent diseases. The efficient identification of the disease depends very much on the …

Breast cancer is the most common type of cancer in women, and early abnormality detection
using mammography can significantly improve breast cancer survival rates. Diverse …

Breast cancer is one of the leading causes of mortality for women all over the world. This
illness significantly threatens the physical and emotional health of women. Breast cancer …

Background: The most important aspect of medical image processing and analysis is image
segmentation. Fundamentally, the outcomes of segmentation have an impact on all …

Detection of metastatic breast cancer lesions is a challenging task in breast cancer
treatment. The recent advancements in deep learning gained attention owing to its …

Mammograms are breast X-ray images and they are used by doctors, among other
purposes, as an effective means of detecting breast cancer. Screening mammography is …

Breast cancer is deadly cancer causing a considerable number of fatalities among women in
worldwide. To enhance patient outcomes as well as survival rates, early and accurate …

Purpose: In the last two decades, computer-aided detection and diagnosis (CAD) systems
have been created to help radiologists discover and diagnose lesions observed on breast …