3 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
Preserving Marker Specificity with Lightweight Channel-Independent Representation Learning
Simon Gutwein, Arthur Longuefosse, Jun Seita +2
Multiplexed tissue imaging measures dozens of protein markers per cell, yet most deep learning models still apply early channel fusion, assuming shared structure across markers. We…
Deep Learning-Based Cross-Anatomy CT Synthesis Using Adapted nnResU-Net with Anatomical Feature Prioritized Loss
Javier Sequeiro González, Arthur Longuefosse, Miguel Díaz Benito +2
We present a patch-based 3D nnUNet adaptation for MR to CT and CBCT to CT image translation using the multicenter SynthRAD2025 dataset, covering head and neck (HN), thorax (TH), an…
Anatomical feature-prioritized loss for enhanced MR to CT translation
Arthur Longuefosse, Baudouin Denis de Senneville, Gael Dournes +3
In medical image synthesis, the precision of localized structural details is crucial, particularly when addressing specific clinical requirements such as the identification and mea…