Advances in medical image analysis with vision transformers: a comprehensive review
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 …
Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
Medical sam adapter: Adapting segment anything model for medical image segmentation
The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …
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 …
Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space
Federated learning allows distributed medical institutions to collaboratively learn a shared
prediction model with privacy protection. While at clinical deployment, the models trained in …
prediction model with privacy protection. While at clinical deployment, the models trained in …
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks
LP Cen, J Ji, JW Lin, ST Ju, HJ Lin, TP Li… - Nature …, 2021 - nature.com
Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses
and appropriate treatments. Single disease-based deep learning algorithms had been …
and appropriate treatments. Single disease-based deep learning algorithms had been …
Applications of deep learning in fundus images: A review
The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …
importance. Due to its powerful performance, deep learning is becoming more and more …
Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening
are being adopted worldwide by medical institutions. In such a context, generating fair and …
are being adopted worldwide by medical institutions. In such a context, generating fair and …
Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation
Medical image analysis plays an important role in clinical diagnosis. In this paper, we
examine the recent Segment Anything Model (SAM) on medical images, and report both …
examine the recent Segment Anything Model (SAM) on medical images, and report both …