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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