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Abstract #2714

New data processing pathway for automatic detection of vascular territories and source vessel locations using random VEASL

Yi Dang 1 , Jia Guo 2 , Jue Zhang 1,3 , and Eric Che Wong 4

1 Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, 2 Department of Bioengineering, University of California San Diego, CA, United States, 3 College of Enigneering, Peking University, Beijing, Beijing, China, 4 Department of Radiology and Psychiatry, University of California San Diego, CA, United States

Random vessel-encoded arterial spin labeling was proposed to simultaneously measure perfusion territories and detect feeding arteries without prior knowledge of their positions. However, the source location of a territory is often blurred so that it is difficult to be manually identified. In addition, mixed supply in one territory may lead to incorrect vessel detection and decoding of perfusion territories. In the present study, we propose a new data processing pathway for R-VEASL based on region growing and matching pursuit for automatic detection of vascular territories and source vessel locations. This RG-MP method also can resolve mixed supplies.

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