2 citations · 3 across the 8 of their papers we have counts for
9 papers · 1 filter
When Misalignment Becomes Supervision: Structured Label Noise in Supervised Synthetic CT Generation
Valentin Boussot, Cedric Hemon, Caroline Lafond +2
Supervised synthetic CT (sCT) generation is commonly trained and evaluated as voxel-wise regression against registered reference CT images. In practice, MRI-CT and CBCT-CT pairs ar…
TotalSynth: Robust Whole-Body Synthetic CT from MRI and CBCT
Valentin Boussot, Cedric Hemon, Anais Barateau +3
Purpose: To develop and evaluate TotalSynth, a reusable pretrained framework for whole-body synthetic CT (sCT) generation from MRI and cone-beam CT (CBCT) images. Materials and Met…
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…
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…
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…
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…
IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration
Valentin Boussot, Cédric Hémon, Jean-Claude Nunes +5
Image registration is fundamental in medical imaging, enabling precise alignment of anatomical structures for diagnosis, treatment planning, image-guided interventions, and longitu…