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 …

[HTML][HTML] 3D deep learning on medical images: a review

SP Singh, L Wang, S Gupta, H Goli, P Padmanabhan… - Sensors, 2020 - mdpi.com
The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …

Artificial intelligence for mammography and digital breast tomosynthesis: current concepts and future perspectives

KJ Geras, RM Mann, L Moy - Radiology, 2019 - pubs.rsna.org
Although computer-aided diagnosis (CAD) is widely used in mammography, conventional
CAD programs that use prompts to indicate potential cancers on the mammograms have not …

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 …

Radiological images and machine learning: trends, perspectives, and prospects

Z Zhang, E Sejdić - Computers in biology and medicine, 2019 - Elsevier
The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

A brief survey on breast cancer diagnostic with deep learning schemes using multi-image modalities

T Mahmood, J Li, Y Pei, F Akhtar, A Imran… - IEEe …, 2020 - ieeexplore.ieee.org
Patients with breast cancer are prone to serious health-related complications with higher
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …

Automated breast cancer detection in mammography using ensemble classifier and feature weighting algorithms

F Yan, H Huang, W Pedrycz, K Hirota - Expert Systems with Applications, 2023 - Elsevier
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 …

A review on automated cancer detection in medical images using machine learning and deep learning based computational techniques: Challenges and …

J Manhas, RK Gupta, PP Roy - Archives of Computational Methods in …, 2022 - Springer
Cancer is one of the most deadly diseases diagnosed among the population across the
globe so far. The number of cases is increasing at a high pace each year that subsequently …

Automatic computer-aided diagnosis system for mass detection and classification in mammography

IA Lbachir, I Daoudi, S Tallal - Multimedia Tools and Applications, 2021 - Springer
Mammography is currently the most powerful technique for early detection of breast cancer.
To assist radiologists to better interpret mammogram images, computer-aided detection and …

[PDF][PDF] Pseudo zernike moment and deep stacked sparse autoencoder for COVID-19 diagnosis

YD Zhang, MA Khan, Z Zhu, SH Wang - Comput Mater Contin, 2021 - academia.edu
(Aim) COVID-19 is an ongoing infectious disease. It has caused more than 107.45 m
confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods …