Abstract #3808

ASL-MRICloud: Towards a comprehensive online tool for ASL data analysis

Yang Li^1,2, Peiying Liu¹, Yue Li³, Hongli Fan¹, Shin-Lei Peng⁴, Denise C. Park⁵, Karen M. Rodrigue⁵, Hangyi Jiang¹, Andreia V. Faria¹, Can Ceritoglu⁶, Michael Miller⁶, Susumu Mori¹, and Hanzhang Lu¹

¹Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Graduate School of Biomedical Sciences, UT Southwestern Medical Center, Dallas, TX, United States, ³AnatomyWorks, LLC, Baltimore, MD, United States, ⁴Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung City, Taiwan, ⁵Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States, ⁶Center for Imaging Science, Johns Hopkins University, Baltimore, MD, United States

ASL has drawn tremendous attention from both research and clinical community during recent years. Therefore, we deployed a cloud-based tool for ASL data analysis on top of MRICloud platform. Different from other downloadable ASL toolboxes, ASL-MRICloud features an automated interface via a web browser for data upload and results download. The computation is performed on the online server. Here we summarized the current functionalities, underlying algorithms, and representative results of ASL-MRICloud.

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