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Abstract #2890

CoverBLIP: scalable iterative matched-filtering for MR Fingerprint recovery

Mohammad Golbabaee1, Zhouye Chen2, Yves Wiaux2, and Michael Davies1

1School of Engineering, University of Edinburgh, Edinburgh, United Kingdom, 2School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom

Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the size and complexity of the fingerprints dictionary. In this abstract we investigate and evaluate the advantages of incorporating an accelerated and scalable Approximate Nearest Neighbour Search (ANNS) scheme based on the Cover trees structure to shortcut the computations of this step within an iterative recovery algorithm and to obtain a good compromise between the computational cost and reconstruction accuracy of the MRF problem.

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