[HTML][HTML] Breast cancer detection and diagnosis using mammographic data: Systematic review
Background Machine learning (ML) has become a vital part of medical imaging research.
ML methods have evolved over the years from manual seeded inputs to automatic …
ML methods have evolved over the years from manual seeded inputs to automatic …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Improved threshold based and trainable fully automated segmentation for breast cancer boundary and pectoral muscle in mammogram images
Segmentation of the breast region and pectoral muscle are fundamental subsequent steps
in the process of Computer-Aided Diagnosis (CAD) systems. Segmenting the breast region …
in the process of Computer-Aided Diagnosis (CAD) systems. Segmenting the breast region …
A review on image-based approaches for breast cancer detection, segmentation, and classification
Z Rezaei - Expert Systems with Applications, 2021 - Elsevier
The breast cancer as the most life-threatening disease among the woman has emerged in
the worldwide. It is supposed that the early testing and treatment for breast cancer detection …
the worldwide. It is supposed that the early testing and treatment for breast cancer detection …
Automated breast cancer detection in mammography using ensemble classifier and feature weighting algorithms
Breast cancer exhibits one of the highest incidence and mortality rates among all cancers
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
Preprocessing of breast cancer images to create datasets for deep-CNN
Breast cancer is the most diagnosed cancer in Australia with crude incidence rates
increasing drastically from 62.8 at ages 35-39 to 271.4 at ages 50-54 (cases per 100,000 …
increasing drastically from 62.8 at ages 35-39 to 271.4 at ages 50-54 (cases per 100,000 …
A hybrid artificial bee colony with whale optimization algorithm for improved breast cancer diagnosis
Breast cancer is the most common among women that leads to death if not diagnosed at
early stages. Early diagnosis plays a vital role in decreasing the mortality rate globally …
early stages. Early diagnosis plays a vital role in decreasing the mortality rate globally …
A hierarchical pipeline for breast boundary segmentation and calcification detection in mammograms
Breast cancer is one of the most common cancer risks to women in the world. Amongst
multiple breast imaging modalities, mammography has been widely used in breast cancer …
multiple breast imaging modalities, mammography has been widely used in breast cancer …
Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network
This paper presents a method for automatic breast pectoral muscle segmentation in
mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired …
mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired …
[HTML][HTML] Deep-LIBRA: An artificial-intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment
Breast density is an important risk factor for breast cancer that also affects the specificity and
sensitivity of screening mammography. Current federal legislation mandates reporting of …
sensitivity of screening mammography. Current federal legislation mandates reporting of …