3 papers
eess.IV2026
Tumor-aware augmentation with task-guided attention analysis improves rectal cancer segmentation from magnetic resonance images
Aneesh Rangnekar, Joao Miranda, Natally Horvat +14
Although self-supervised pretraining is expected to learn broadly transferable representations, its effectiveness across imaging modalities substantially different from the pretrai…
cs.CV2026
Benchmarking transferability of SSL pretraining to same and different modality segmentation tasks
Jue Jiang, Harini Veeraraghavan
Methods: Nine SSL methods spanning four pretext-task families were pretrained from scratch using the same 10{,}412 3D CT scans (1.89~M 2D axial slices) covering varied disease site…
cs.CV2026
Prediction of Rectal Cancer Regrowth from Longitudinal Endoscopy
Jorge Tapias Gomez, Despoina Kanata, Aneesh Rangnekar +8
Clinical trial studies indicate benefit of watch-and-wait (WW) surveillance for patients with rectal cancer showing a complete or near clinical response (CR) directly after treatme…