Transformers in medical imaging: A survey

F Shamshad, S Khan, SW Zamir, MH Khan… - Medical Image …, 2023 - Elsevier
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Breast cancer detection using artificial intelligence techniques: A systematic literature review

AB Nassif, MA Talib, Q Nasir, Y Afadar… - Artificial intelligence in …, 2022 - Elsevier
Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has
been developed for it. Breast cancer is one of the most common cancer types. According to …

[HTML][HTML] Computational approaches to explainable artificial intelligence: advances in theory, applications and trends

JM Górriz, I Álvarez-Illán, A Álvarez-Marquina, JE Arco… - Information …, 2023 - Elsevier
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

[HTML][HTML] Artificial intelligence and computational pathology

M Cui, DY Zhang - Laboratory Investigation, 2021 - Elsevier
Data processing and learning has become a spearhead for the advancement of medicine,
with pathology and laboratory medicine has no exception. The incorporation of scientific …

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] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis

M Salvi, UR Acharya, F Molinari… - Computers in Biology and …, 2021 - Elsevier
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm

EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2022 - Springer
Breast cancer is the second leading cause of death in women; therefore, effective early
detection of this cancer can reduce its mortality rate. Breast cancer detection and …

Deep learning to improve breast cancer detection on screening mammography

L Shen, LR Margolies, JH Rothstein, E Fluder… - Scientific reports, 2019 - nature.com
The rapid development of deep learning, a family of machine learning techniques, has
spurred much interest in its application to medical imaging problems. Here, we develop a …

[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 …

[HTML][HTML] Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art

I Sechopoulos, J Teuwen, R Mann - Seminars in cancer biology, 2021 - Elsevier
Screening for breast cancer with mammography has been introduced in various countries
over the last 30 years, initially using analog screen-film-based systems and, over the last 20 …