13 citations · 18 across the 2 of their papers we have counts for
5 papers
Guidance-Coupled Nullspace Drifting for One-Step Medical Image Reconstruction
M. Tuna Alatan, Agah Server Tapan, Şaban Öztürk +4
Generative reconstruction can recover high-quality images from undersampled acquisitions, but state-of-the-art generative priors commonly rely on iterative sampling. Reducing the n…
Generative Autoregressive Transformers for Model-Agnostic Federated MRI Reconstruction
Valiyeh A. Nezhad, Gokberk Elmas, Bilal Kabas +3
While learning-based models hold great promise for MRI reconstruction, single-site models trained on limited local datasets often show poor generalization. This has motivated colla…
Physics-Driven Autoregressive State Space Models for Medical Image Reconstruction
Bilal Kabas, Fuat Arslan, Valiyeh A. Nezhad +3
Medical image reconstruction from undersampled acquisitions is an ill-posed inverse problem requiring accurate recovery of anatomical structures from incomplete measurements. Physi…
Self-Consistent Recursive Diffusion Bridge for Medical Image Translation
Fuat Arslan, Bilal Kabas, Onat Dalmaz +2
Denoising diffusion models (DDM) have gained recent traction in medical image translation given improved training stability over adversarial models. DDMs learn a multi-step denoisi…
I2I-Mamba: Multi-modal medical image synthesis via selective state space modeling
Omer F. Atli, Bilal Kabas, Fuat Arslan +4
Multi-modal medical image synthesis involves nonlinear transformation of tissue signals between source and target modalities, where tissues exhibit contextual interactions across d…