Resolving to super resolution multi-dimensional diffusion imaging (Super-MUDI)

Vishwesh Nath, Marco Pizzolato, Marco Palombo, Noemi Gyori, Kurt G. Schilling, Colin H. Hansen, Yang Qi, Praitayini Kanakaraj, Bennett A. Landman, Soumick Chatterjee, Alessandro Sciarra, Max Duennwald, Steffen Oeltze-Jafra, Andreas Nuernberger, Oliver Speck, Tomasz Pieciak, Marcin Baranek, Kamil Bartocha, Dominika Ciupek, Fabian BoguszAzam Hamidinekoo, Maryam Afzali, Harry Lin, Danny C. Alexander, Haoyu Lan, Farshid Sepehrband, Zifei Liang, Tung-Yeh Wu, Ching-Wei Su, Qian-Hua Wu , Zi-You Liu, Yi-Ping Chao, Enes Albay, Gozde Unal, Dmytro Pylypenko, Xinyu Ye, Fan Zhang, Jana Hutter

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review


Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical modality that allows characterization of microstructure of the nervous tissue in the human brain. Recent multi-parametric acquisitions expand parameter space to b-values, gradient directions, inversion and echo times. The required long scanning time could be shortened by acquiring at lower resolutions while superesolving the images during post-processing. This work embodies the evaluation of an open challenge where the objective was to upsample multi dimensional data encoding simultaneously T1, T2* and diffusion contrast to the natively acquired voxel resolution from two different down-sampled sets of the data (isotropic down-sampled and anisotropic down-sampled).
Original languageEnglish
Publication date2021
Number of pages3
Publication statusPublished - 2021
Event2021 ISMRM & SMRT Annual Meeting & Exhibition - Online
Duration: 15 May 202120 May 2021


Conference2021 ISMRM & SMRT Annual Meeting & Exhibition


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