Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15699-1_32
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dc.titleLevel set diffusion for MRE image enhancement
dc.contributor.authorLi, B.N.
dc.contributor.authorChui, C.K.
dc.contributor.authorOng, S.H.
dc.contributor.authorChang, S.
dc.contributor.authorKobayashi, E.
dc.date.accessioned2014-04-24T08:36:12Z
dc.date.available2014-04-24T08:36:12Z
dc.date.issued2010
dc.identifier.citationLi, B.N.,Chui, C.K.,Ong, S.H.,Chang, S.,Kobayashi, E. (2010). Level set diffusion for MRE image enhancement. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6326 LNCS : 305-313. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-15699-1_32" target="_blank">https://doi.org/10.1007/978-3-642-15699-1_32</a>
dc.identifier.isbn3642156983
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/51200
dc.description.abstractMagnetic resonance elastography (MRE) is an emerging technique for noninvasive imaging of tissue elasticity. Proprietary algorithms are used to reconstruct tissue elasticity from the images of wave propagation within soft tissue. Elasticity reconstruction suffers from interfering noise and outliers. The interference causes biased elasticity and undesired artifacts in the reconstructed elasticity map. Anisotropic geometric diffusion is able to suppress image noise while enhance inherent features. Therefore we integrate anisotropic diffusion with level set methods for numerical enhancement of MRE wave images. Performance evaluation of the proposed level set diffusion (LSD) approach was conducted on both synthetic and real MRE datasets. Experimental results confirm the effectiveness of LSD for MRE image enhancement and direct inversion. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-15699-1_32
dc.sourceScopus
dc.subjectAnisotropic diffusion
dc.subjectimage enhancement
dc.subjectlevel set methods
dc.subjectmagnetic resonance elastography (MRE)
dc.subjectnoise suppression
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/978-3-642-15699-1_32
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6326 LNCS
dc.description.page305-313
dc.identifier.isiutNOT_IN_WOS
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