One model to unite them all: Personalized federated learning of multi-contrast MRI synthesis-Reference-Cited by-同舟云学术

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

Published:2024-05 Issue: Volume:94 Page:103121
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Dalmaz Onat^ORCID,Mirza Muhammad U.,Elmas Gokberk^ORCID,Ozbey Muzaffer^ORCID,Dar Salman U.H.^ORCID,Ceyani Emir^ORCID,Oguz Kader K.^ORCID,Avestimehr Salman^ORCID,Çukur Tolga^ORCID

Publisher

Elsevier BV

Reference115 articles.

1. Grainger & Allison’s Diagnostic Radiology;Adam,2014

2. Missing data;Altman;BMJ,2007

3. MedGAN: Medical image translation using GANs;Armanious;Comput. Med. Imaging Graph.,2020

4. Magnetic Resonance Imaging of the Brain and Spine;Atlas,2009

5. Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features;Bakas;Sci. Data,2017

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Model-based federated learning for accurate MR image reconstruction from undersampled k-space data;Computers in Biology and Medicine;2024-09

2. Multi-Contrast MR Image Synthesis with a Brownian Diffusion Model;2024 32nd Signal Processing and Communications Applications Conference (SIU);2024-05-15

3. Super Resolution MRI via Upscaling Diffusion Bridges;2024 32nd Signal Processing and Communications Applications Conference (SIU);2024-05-15

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