8 papers
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…
Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report
Viktor Rogowski, Maarten L. Terpstra, Niklas Wahl +30
Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acqui…
Assessing Pancreatic Ductal Adenocarcinoma Vascular Invasion: the PDACVI Benchmark
M. Riera-MarÃn, O. K. Sikha, J. RodrÃguez-Comas +23
Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion…
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.…
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…
KonfAI: A Modular and Fully Configurable Framework for Deep Learning in Medical Imaging
Valentin Boussot, Jean-Louis Dillenseger
KonfAI is a modular, extensible, and fully configurable deep learning framework specifically designed for medical imaging tasks. It enables users to define complete training, infer…