1 citations · 1 across the 16 of their papers we have counts for
4 papers · 1 filter
BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation
Max Van Puyvelde, Ibrahim Gulluk, Wim Van Criekinge +1
Three-dimensional (3D) brain MRI is central to clinical neurology and neuro-oncology, where generative models could augment under-represented cohorts, simulate disease trajectories…
Discrete Diffusion Language Models for Interactive Radiology Report Drafting
Max Van Puyvelde, Halil Ibrahim Gulluk, Wim Van Criekinge +1
Diffusion language models, which generate text by denoising a token canvas bidirectionally instead of emitting tokens left to right, have become competitive with autoregressive (AR…
OpenMedQ: Broad Open Pretraining for Medical Vision-Language Models
Ibrahim Gulluk, Max Van Puyvelde, Olivier Gevaert
We present OpenMedQ, a medical vision-language model pretrained on the broadest fully-open medical mix to date: 14 datasets totaling ~3.35M pretraining samples spanning pathology,…
SDR: Set-Distance Rewards for Radiology Report Generation
Halil Ibrahim Gulluk, Max Van Puyvelde, Wim Van Criekinge +1
Reinforcement learning with verifiable rewards has rapidly advanced reasoning in vision--language models. However, for chest X-ray report generation, the standard rewards (i.e. exa…