Method: ProRSeg was trained using 5-fold cross-validation with 110
T2-we...
Vision transformers, with their ability to more efficiently model long-r...
Image-guided adaptive lung radiotherapy requires accurate tumor and orga...
Accurate and robust segmentation of lung cancers from CTs is needed to m...
Although deep convolutional networks have been widely studied for head a...
Despite the widespread availability of in-treatment room cone beam compu...
Our contribution is a unified cross-modality feature disentagling approa...
We developed a new joint probabilistic segmentation and image distributi...
We implemented and evaluated a multiple resolution residual network (MRR...
We developed a new and computationally simple local block-wise self atte...
Lung tumors, especially those located close to or surrounded by soft tis...
Lack of large expert annotated MR datasets makes training deep learning
...