Harnessing the power of pre-training on large-scale datasets like ImageN...
Transformers have recently shown promise for medical image applications,...
In the past, optimization-based registration models have used
spatially-...
Artificial Intelligence (AI) is having a tremendous impact across most a...
Head and neck tumor segmentation challenge (HECKTOR) 2022 offers a platf...
Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a
...
Ischemic Stroke Lesion Segmentation challenge (ISLES 2022) offers a plat...
Semantic segmentation of 3D medical images is a challenging task due to ...
In the last decade, convolutional neural networks (ConvNets) have domina...
In the last decade, convolutional neural networks (ConvNets) have domina...
Recently, neural architecture search (NAS) has been applied to automatic...
Accuracy and consistency are two key factors in computer-assisted magnet...
Domain shift is a major problem for deploying deep networks in clinical
...
Medical images are increasingly used as input to deep neural networks to...
Medical images are often used to detect and characterize pathology and
d...
Optical coherence tomography (OCT) is a noninvasive imaging modality whi...
With the introduction of spectral-domain optical coherence tomography
(S...