Breast cancer detection using deep learning: Datasets, methods, and challenges ahead

RA Dar, M Rasool, A Assad - Computers in biology and medicine, 2022‏ - Elsevier
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …

A comprehensive review on breast cancer detection, classification and segmentation using deep learning

B Abhisheka, SK Biswas, B Purkayastha - Archives of Computational …, 2023‏ - Springer
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 …

Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021‏ - Elsevier
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 …

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

NIR Yassin, S Omran, EMF El Houby… - Computer methods and …, 2018‏ - Elsevier
Background and objective The high incidence of breast cancer in women has increased
significantly in the recent years. Physician experience of diagnosing and detecting breast …

Inbreast: toward a full-field digital mammographic database

IC Moreira, I Amaral, I Domingues, A Cardoso… - Academic radiology, 2012‏ - Elsevier
RATIONALE AND OBJECTIVES: Computer-aided detection and diagnosis (CAD) systems
have been developed in the past two decades to assist radiologists in the detection and …

Survey on machine learning and deep learning applications in breast cancer diagnosis

G Chugh, S Kumar, N Singh - Cognitive Computation, 2021‏ - Springer
Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …

Three‐class mammogram classification based on descriptive CNN features

MM Jadoon, Q Zhang, IU Haq, S Butt… - BioMed research …, 2017‏ - Wiley Online Library
In this paper, a novel classification technique for large data set of mammograms using a
deep learning method is proposed. The proposed model targets a three‐class classification …

Automated breast mass classification system using deep learning and ensemble learning in digital mammogram

SJ Malebary, A Hashmi - IEEE Access, 2021‏ - ieeexplore.ieee.org
In recent years, deep learning techniques are employed in the mammography processing
field to reduce radiologists' costs. Existing breast mass classification systems are …

Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey

P Oza, P Sharma, S Patel, P Kumar - Neural computing and applications, 2022‏ - Springer
Advances in deep learning networks, especially deep convolutional neural networks
(DCNNs), are causing remarkable breakthroughs in radiology and imaging sciences. These …

A Technical Review of Convolutional Neural Network‐Based Mammographic Breast Cancer Diagnosis

L Zou, S Yu, T Meng, Z Zhang… - … methods in medicine, 2019‏ - Wiley Online Library
This study reviews the technique of convolutional neural network (CNN) applied in a specific
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …