1.2k citations · 1.7k across the 23 of their papers we have counts for
4 papers · 1 filter
Image-level supervision and self-training for transformer-based cross-modality tumor segmentation
Malo de Boisredon, Eugene Vorontsov, William Trung Le +1
Deep neural networks are commonly used for automated medical image segmentation, but models will frequently struggle to generalize well across different imaging modalities. This is…
End-to-end Deformable Attention Graph Neural Network for Single-view Liver Mesh Reconstruction
Matej Gazda, Peter Drotar, Liset Vazquez Romaguera +1
Intensity modulated radiotherapy (IMRT) is one of the most common modalities for treating cancer patients. One of the biggest challenges is precise treatment delivery that accounts…
Comparing 3D deformations between longitudinal daily CBCT acquisitions using CNN for head and neck radiotherapy toxicity prediction
William Trung Le, Chulmin Bang, Philippine Cordelle +4
Adaptive radiotherapy is a growing field of study in cancer treatment due to it's objective in sparing healthy tissue. The standard of care in several institutions includes longitu…
Prediction of a T-cell/MHC-I-based immune profile for colorectal liver metastases from CT images using ensemble learning
Ralph Saber, David Henault, Rolando Rebolledo +2
Colorectal cancer liver metastases (CLM) are the most common type of distant metastases originating from the abdomen and are characterized by a high recurrence rate after curative…