Deep neural networks (DNNs) utilized recently are physically deployed wi...
We introduce a novel Region-based contrastive pretraining for Medical Im...
The accuracy of predictive models for solitary pulmonary nodule (SPN)
di...
Vision transformers (ViTs) have quickly superseded convolutional network...
Non-contrast computed tomography (NCCT) is commonly acquired for lung ca...
Efficiently quantifying renal structures can provide distinct spatial co...
Multiplex immunofluorescence (MxIF) is an emerging imaging technique tha...
Data from multi-modality provide complementary information in clinical
p...
Contrastive learning has shown superior performance in embedding global ...
The construction of three-dimensional multi-modal tissue maps provides a...
Performing coarse-to-fine abdominal multi-organ segmentation facilitates...
Segmentation of abdominal computed tomography(CT) provides spatial conte...
Abdominal multi-organ segmentation of computed tomography (CT) images ha...
Dynamic contrast enhanced computed tomography (CT) is an imaging techniq...
Human in-the-loop quality assurance (QA) is typically performed after me...