9 citations · 30 across the 9 of their papers we have counts for
6 papers · 1 filter
Stochastic Finite-Transition Learning and Exploration for Accelerated MRI Reconstruction
Muhammad Usama Mirza, Esin Öztürk Işık, Tolga Çukur
Generative MRI reconstruction maps an initial source distribution to the target image distribution along a learned recovery trajectory. Common generative methods, such as diffusion…
A Tutorial on MRI Reconstruction: From Modern Methods to Clinical Implications
Tolga Çukur, Salman U. H. Dar, Valiyeh Ansarian Nezhad +4
MRI is an indispensable clinical tool, offering a rich variety of tissue contrasts to support broad diagnostic and research applications. Clinical exams routinely acquire multiple…
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…
DenoMamba: A fused state-space model for low-dose CT denoising
Şaban Öztürk, Oğuz Can Duran, Tolga Çukur
Low-dose computed tomography (LDCT) lower potential risks linked to radiation exposure while relying on advanced denoising algorithms to maintain diagnostic quality in reconstructe…
HydraViT: Adaptive Multi-Branch Transformer for Multi-Label Disease Classification from Chest X-ray Images
Şaban Öztürk, M. Yiğit Turalı, Tolga Çukur
Chest X-ray is an essential diagnostic tool in the identification of chest diseases given its high sensitivity to pathological abnormalities in the lungs. However, image-driven dia…