Advances in medical image analysis with vision transformers: a comprehensive review

R Azad, A Kazerouni, M Heidari, EK Aghdam… - Medical Image …, 2024 - Elsevier
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives

J Li, J Chen, Y Tang, C Wang, BA Landman… - Medical image …, 2023 - Elsevier
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

A whole-body FDG-PET/CT dataset with manually annotated tumor lesions

S Gatidis, T Hepp, M Früh, C La Fougère, K Nikolaou… - Scientific Data, 2022 - nature.com
We describe a publicly available dataset of annotated Positron Emission Tomography/
Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG) …

Deep learning techniques for diabetic retinopathy classification: A survey

MZ Atwany, AH Sahyoun, M Yaqub - IEEE Access, 2022 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a degenerative disease that impacts the eyes and is a
consequence of Diabetes mellitus, where high blood glucose levels induce lesions on the …

[HTML][HTML] Machine learning empowering personalized medicine: A comprehensive review of medical image analysis methods

I Galić, M Habijan, H Leventić, K Romić - Electronics, 2023 - mdpi.com
Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …

Generative adversarial networks in medicine: important considerations for this emerging innovation in artificial intelligence

PS Paladugu, J Ong, N Nelson, SA Kamran… - Annals of biomedical …, 2023 - Springer
The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the
field of medicine. Although highly effective, the rapid expansion of this technology has …

A foundation language-image model of the retina (flair): Encoding expert knowledge in text supervision

J Silva-Rodriguez, H Chakor, R Kobbi, J Dolz… - Medical Image …, 2025 - Elsevier
Foundation vision-language models are currently transforming computer vision, and are on
the rise in medical imaging fueled by their very promising generalization capabilities …

Multi-label retinal disease classification using transformers

MA Rodríguez, H AlMarzouqi… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Early detection of retinal diseases is one of the most important means of preventing partial or
permanent blindness in patients. In this research, a novel multi-label classification system is …

EyeDeep-Net: A multi-class diagnosis of retinal diseases using deep neural network

N Sengar, RC Joshi, MK Dutta, R Burget - Neural Computing and …, 2023 - Springer
Retinal images are a key element for ophthalmologists in diagnosing a variety of eye
illnesses. The retina is vulnerable to microvascular changes as a result of many retinal …

Multi-class disease detection using deep learning and human brain medical imaging

F Yousaf, S Iqbal, N Fatima, T Kousar… - … Signal Processing and …, 2023 - Elsevier
Medical imaging and deep learning methods have significantly improved the early detection
of brain diseases like tumors and Ischemic stroke with higher accuracy. Machine learning …