3 citations · 4 across the 4 of their papers we have counts for
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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…
CT evaluation of 2D and 3D holistic deep learning methods for the volumetric segmentation of airway lesions
Amel Imene Hadj Bouzid, Baudouin Denis de Senneville, Fabien Baldacci +4
This research embarked on a comparative exploration of the holistic segmentation capabilities of Convolutional Neural Networks (CNNs) in both 2D and 3D formats, focusing on cystic…