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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 …
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
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
A whole-body FDG-PET/CT dataset with manually annotated tumor lesions
We describe a publicly available dataset of annotated Positron Emission Tomography/
Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG) …
Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG) …
Deep learning techniques for diabetic retinopathy classification: A survey
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 …
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
Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …
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
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 …
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 …
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 …
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
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 …
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
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 …
of brain diseases like tumors and Ischemic stroke with higher accuracy. Machine learning …