Abstract #3389
Kd-tree for Dictionary Matching in Magnetic Resonance Fingerprinting
Nicolas Pannetier 1,2 and Norbert Schuff 1,2
1
Radiology, UCSF, San Francisco, California,
United States,
2
VAMC,
San Francisco, CA, United States
We evaluate the use of kd-tree (a space partitioning
data structure) to speed-up the matching process in
magnetic resonance fingerprinting. We found that, in
combination with PCA reduction, the matching time can be
reduced by 2 to 3 order of magnitude while preserving
the accuracy. The matching time, however, increases with
noise level and the PCA threshold remains a key element
to tune to achieve the best performance.
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