Detection of small cerebral lesions using multi-component MR Fingerprinting with local joint sparsity

Research output: Contribution to conferenceAbstractScientific

Abstract

We propose a novel multi-component analysis for MR fingerprinting that enables detection of small lesions, while taking partial volume effects into account. The algorithm uses a joint sparsity constraint limiting the number of components in local regions. It is evaluated in simulations and on MRF-EPI data from a patient with multiple sclerosis (MS). MS-lesions are separated from other tissues based on having increased T2* relaxation times. The improved sensitivity to multiple components makes it possible to detect components with long relaxation times within the lesion, possibly increasing our insight into these small pathologies.
Original languageEnglish
Number of pages10
Publication statusPublished - 2020
EventISMRM (International Society for Magnetic Resonance and Medicine) Virtual meeting: ISMRM & SMRT Virtual Conference & Exhibition -
Duration: 8 Aug 202014 Aug 2020
Conference number: 28
https://www.ismrm.org/20m/ (Link event Annual Meeting ISMRM 2020)

Conference

ConferenceISMRM (International Society for Magnetic Resonance and Medicine) Virtual meeting
Period8/08/2014/08/20
Internet address

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