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cs.CV2026

An Uncertainty Estimation Framework for Dose Accumulation in Adaptive Radiotherapy: Application to CBCT-Guided Radiotherapy for Cervical Cancer

Cedric Hemon, Delphine Lebret, Jean-Claude Nunes +8

Background and purpose: oART enables daily plan adaptation to interfraction anatomical variations, but cumulative dose estimation remains limited by DIR, segmentation, and anatomic…

cs.CV2026

Assessing Pancreatic Ductal Adenocarcinoma Vascular Invasion: the PDACVI Benchmark

M. Riera-Marín, O. K. Sikha, J. Rodríguez-Comas +23

Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion…

cs.CV2025

Fine-tuning Segment Anything for Real-Time Tumor Tracking in Cine-MRI

Valentin Boussot, Cédric Hémon, Jean-Claude Nunes +1

In this work, we address the TrackRAD2025 challenge of real-time tumor tracking in cine-MRI sequences of the thoracic and abdominal regions under strong data scarcity constraints.…

cs.CV2025

Why Registration Quality Matters: Enhancing sCT Synthesis with IMPACT-Based Registration

Valentin Boussot, Cédric Hémon, Jean-Claude Nunes +1

We participated in the SynthRAD2025 challenge (Tasks 1 and 2) with a unified pipeline for synthetic CT (sCT) generation from MRI and CBCT, implemented using the KonfAI framework. O…

cs.CV2025

Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results

Meritxell Riera-Marin, Sikha O K, Julia Rodriguez-Comas +29

Deep learning (DL) has become the dominant approach for medical image segmentation, yet ensuring the reliability and clinical applicability of these models requires addressing key…

cs.CV2025

Implicit Shape-Prior for Few-Shot Assisted 3D Segmentation

Mathilde Monvoisin, Louise Piecuch, Blanche Texier +7

The objective of this paper is to significantly reduce the manual workload required from medical professionals in complex 3D segmentation tasks that cannot be yet fully automated.…