1 code implementation • 2 Aug 2023 • Muhammad U. Mirza, Onat Dalmaz, Hasan A. Bedel, Gokberk Elmas, Yilmaz Korkmaz, Alper Gungor, Salman UH Dar, Tolga Çukur
Instead of the target transformation from undersampled to fully-sampled data required for MRI reconstruction, common diffusion priors are trained to learn a task-agnostic transformation from an asymptotic start-point of Gaussian noise onto the finite end-point of fully-sampled data.
no code implementations • 25 Jan 2023 • Sevcan Turk, Ahmet Demirkaya, M Yigit Turali, Cenk Hepdurgun, Salman UH Dar, Ahmet K Karabulut, Aynur Azizova, Mehmet Orman, Ipek Tamsel, Ustun Aydingoz, Mehmet Argin, Tolga Cukur
Results: JointNET differentiated active inflammation from radiographs with a mean AUROC of 89. 2 (95% CI:86. 8%, 91. 7%).
1 code implementation • 6 Jan 2023 • Salman UH Dar, Şaban Öztürk, Muzaffer Özbey, Tolga Çukur
To alleviate error propagation, PSFNet combines its SS and SG priors via a novel parallel-stream architecture with learnable fusion parameters.
1 code implementation • 17 Jul 2022 • Muzaffer Özbey, Onat Dalmaz, Salman UH Dar, Hasan A Bedel, Şaban Özturk, Alper Güngör, Tolga Çukur
Extensive assessments are reported on the utility of SynDiff against competing GAN and diffusion models in multi-contrast MRI and MRI-CT translation.
Ranked #7 on Image-to-Image Translation on IXI
1 code implementation • 13 Jul 2022 • Onat Dalmaz, Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman UH Dar, Emir Ceyani, Salman Avestimehr, Tolga Çukur
As such, pFLSynth enables training of a unified synthesis model that can reliably generalize across multiple sites and translation tasks.
1 code implementation • 12 Jul 2022 • Alper Güngör, Salman UH Dar, Şaban Öztürk, Yilmaz Korkmaz, Gokberk Elmas, Muzaffer Özbey, Tolga Çukur
A two-phase reconstruction is executed following training: a rapid-diffusion phase that produces an initial reconstruction with the trained prior, and an adaptation phase that further refines the result by updating the prior to minimize data-consistency loss.
1 code implementation • 8 Feb 2022 • Gokberk Elmas, Salman UH Dar, Yilmaz Korkmaz, Emir Ceyani, Burak Susam, Muzaffer Özbey, Salman Avestimehr, Tolga Çukur
Specificity in the prior is preserved via a mapper subnetwork that produces site-specific latents.
1 code implementation • 15 May 2021 • Yilmaz Korkmaz, Salman UH Dar, Mahmut Yurt, Muzaffer Özbey, Tolga Çukur
Supervised reconstruction models are characteristically trained on matched pairs of undersampled and fully-sampled data to capture an MRI prior, along with supervision regarding the imaging operator to enforce data consistency.