CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery

Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Michael Davies

Research output: Contribution to conferenceAbstractpeer-review

Abstract / Description of output

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.
Original languageEnglish
Publication statusPublished - 6 Sept 2018
Event2018 International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting - Paris, France
Duration: 16 Jun 201821 Jun 2018

Conference

Conference2018 International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting
Country/TerritoryFrance
CityParis
Period16/06/1821/06/18

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