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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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