[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review

K Loizidou, R Elia, C Pitris - Computers in Biology and Medicine, 2023 - Elsevier
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …

Artificial intelligence for breast cancer analysis: Trends & directions

SM Shah, RA Khan, S Arif, U Sajid - Computers in Biology and Medicine, 2022 - Elsevier
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …

Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach

T Mahmood, J Li, Y Pei, F Akhtar, MU Rehman… - Plos one, 2022 - journals.plos.org
Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally.
Breast cancer detection needs accurate mammography interpretation and analysis, which is …

Recent advancements and future prospects in active deep learning for medical image segmentation and classification

T Mahmood, A Rehman, T Saba, L Nadeem… - IEEE …, 2023 - ieeexplore.ieee.org
Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …

An automated in-depth feature learning algorithm for breast abnormality prognosis and robust characterization from mammography images using deep transfer …

T Mahmood, J Li, Y Pei, F Akhtar - Biology, 2021 - mdpi.com
Simple Summary Diagnosing breast cancer masses and calcification clusters is crucial in
mammography, which reduces disease consequences and initiates treatment at an early …

Breast cancer diagnosis based on IoT and deep transfer learning enabled by fog computing

A Pati, M Parhi, BK Pattanayak, D Singh, V Singh… - Diagnostics, 2023 - mdpi.com
Across all countries, both developing and developed, women face the greatest risk of breast
cancer. Patients who have their breast cancer diagnosed and staged early have a better …

Research on object detection and recognition method for UAV aerial images based on improved YOLOv5

H Zhang, F Shao, X He, Z Zhang, Y Cai, S Bi - Drones, 2023 - mdpi.com
In this paper, an object detection and recognition method based on improved YOLOv5 is
proposed for application on unmanned aerial vehicle (UAV) aerial images. Firstly, we …

CanDiag: fog empowered transfer deep learning based approach for cancer diagnosis

A Pati, M Parhi, BK Pattanayak, B Sahu, S Khasim - Designs, 2023 - mdpi.com
Breast cancer poses the greatest long-term health risk to women worldwide, in both
industrialized and developing nations. Early detection of breast cancer allows for treatment …

A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics

HM Rai, J Yoo - Journal of Cancer Research and Clinical Oncology, 2023 - Springer
Purpose There are millions of people who lose their life due to several types of fatal
diseases. Cancer is one of the most fatal diseases which may be due to obesity, alcohol …

Harnessing the power of radiomics and deep learning for improved breast cancer diagnosis with multiparametric breast mammography

T Mahmood, T Saba, A Rehman, FS Alamri - Expert Systems with …, 2024 - Elsevier
Breast cancer, with its high mortality, faces diagnostic challenges due to variability in
mammography quality and breast densities, leading to inconsistencies in radiological …