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Abstract #3808

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

Yang Li1,2, 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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