Abstract #0103

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

Vishwesh Nath¹, Marco Pizzolato^2,3, Marco Palombo⁴, Noemi Gyori⁴, Kurt G Schilling⁵, Colin Hansen⁶, Qi Yang⁶, Praitayini Kanakaraj⁶, Bennett A Landman⁶, Soumick Chatterjee⁷, Alessandro Sciarra⁷, Max Duennwald⁷, Steffen Oeltze-Jafra⁷, Andreas Nuernberger⁷, Oliver Speck⁷, Tomasz Pieciak ⁸, Marcin Baranek⁸, Kamil Bartocha⁸, Dominika Ciupek⁸, Fabian Bogusz⁸, Azam Hamidinekoo⁹, Maryam Afzali ¹⁰, Harry Lin⁴, Danny C Alexander⁴, Haoyu Lan¹¹, Farshid Sepehrband¹¹, Zifei Liang¹², Tung-Yeh Wu¹³, Ching-Wei Su¹³, Qian-Hua Wu¹³, Zi-You Liu¹³, Yi-Ping Chao¹³, Enes Albay¹⁴, Gozde Unal¹⁴, Dmytro Pylypenko¹³, Xinyu Ye¹³, Fan Zhang¹⁵, and Jana Hutter¹⁶

¹NVIDIA Corporation, Bethesda, MD, United States, ²Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark, ³École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴CMIC, University College London, London, United Kingdom, ⁵Institute of Imaging Science, Vanterbilt University, Nashville, TN, United States, ⁶Department of Computer Science, Vanterbilt University, Nashville, TN, United States, ⁷Otto von Guericke University, Magdeburg, Germany, ⁸AGH University of Science and Technology, Krakow, Poland, ⁹Institute of Cancer Research, London, United Kingdom, ¹⁰CUBRIC, Cardiff University, Cardiff, United Kingdom, ¹¹University of Southern California, Los Angeles, CA, United States, ¹²NYU Langone, New York, NY, United States, ¹³Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, ¹⁴Istanbul Technical University, Istanbul, Turkey, ¹⁵Harvard Medical School, Boston, MA, United States, ¹⁶Centre for Medical Engineering, King's College London, London, United Kingdom

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).

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