Author

C. Hémon

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Preprint Sep 2026

TotalSynth: Robust Whole-Body Synthetic CT from MRI and CBCT

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 Methods: In this retrospective technical study, the dataset was assembled between 2020 and 2026 from SynthRAD challenge data, four prostate coh...

Valentin Boussot, C. Hémon, Anaïs Barateau et al. · 0 citations

Preprint Sep 2026

When Misalignment Becomes Supervision: Structured Label Noise in Supervised Synthetic CT Generation

To mitigate the limits of voxel-wise supervision, a perceptual loss computed in the feature space of a pretrained Segment Anything encoder improves downstream segmentation and yields sharper, more structurally coherent sCT.

Valentin Boussot, C. Hémon, C. Lafond et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Extending TotalSegmentator: Predicting Patient and Acquisition Characteristics from CT and MR Images

One 3D multitask model per modality can rapidly recover patient and acquisition characteristics from heterogeneous CT and MR examinations and outperformed a segmentation-derived XGBoost baseline for all four core targets in both modalities.

J. Wasserthal, Joshy Cyriac, Michael Bach et al. · 0 citations