Gökberk Elmas

According to our database, Gökberk Elmas authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

One model to unite them all: Personalized federated learning of multi-contrast MRI synthesis.

Onat Dalmaz, Muhammad Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman Ul Hassan Dar, Emir Ceyani, Kader Karli Oguz, Salman Avestimehr, Tolga Çukur

Medical Image Anal., 2024

Generalizable Deep MRI Reconstruction with Cross-Site Data Synthesis.

Valiyeh Ansarian Nezhad, Gökberk Elmas, Fuat Arslan, Bilal Kabas, Tolga Çukur

Proceedings of the 32nd Signal Processing and Communications Applications Conference, 2024

2023

Adaptive diffusion priors for accelerated MRI reconstruction.

Alper Güngör, Salman Ul Hassan Dar, Saban Öztürk, Yilmaz Korkmaz, Hasan Atakan Bedel, Gökberk Elmas, Muzaffer Özbey, Tolga Çukur

Medical Image Anal., August, 2023

Federated Learning of Generative Image Priors for MRI Reconstruction.

Gökberk Elmas, Salman Ul Hassan Dar, Yilmaz Korkmaz, Emir Ceyani, Burak Susam, Muzaffer Özbey, Salman Avestimehr, Tolga Çukur

IEEE Trans. Medical Imaging, 2023

Denoising Diffusion Adversarial Models for Unconditional Medical Image Generation.

Onat Dalmaz, Baturay Saglam, Gökberk Elmas, Muhammad Mirza, Tolga Çukur

Proceedings of the 31st Signal Processing and Communications Applications Conference, 2023

2022

One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis.

Onat Dalmaz, Muhammad Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman Ul Hassan Dar, Emir Ceyani, Salman Avestimehr, Tolga Çukur

CoRR, 2022

Adaptive Diffusion Priors for Accelerated MRI Reconstruction.

Salman Ul Hassan Dar, Saban Öztürk, Yilmaz Korkmaz, Gökberk Elmas, Muzaffer Özbey, Alper Güngör, Tolga Çukur

CoRR, 2022

A Specificity-Preserving Generative Model for Federated MRI Translation.

Onat Dalmaz, Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman Ul Hassan Dar, Tolga Çukur

Proceedings of the Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, 2022