most citedA Normalized Fully Convolutional Approach to Head and Neck Cancer Outcome Prediction

4 citations · 6 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2023

Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction

Mohamed El Amine Elforaici, Emmanuel Montagnon, Francisco Perdigon Romero +7

Colorectal liver metastases (CLM) significantly impact colon cancer patients, influencing survival based on systemic chemotherapy response. Traditional methods like tumor grading s…

cs.CV20231 cited

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…

cs.CV20231 cited

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…

eess.IV20204 cited

A Normalized Fully Convolutional Approach to Head and Neck Cancer Outcome Prediction

William Le, Francisco Perdigón Romero, Samuel Kadoury

In medical imaging, radiological scans of different modalities serve to enhance different sets of features for clinical diagnosis and treatment planning. This variety enriches the…