Differentiation of multiple sclerosis lesions and low-grade brain tumors on MRS data: machine learning approaches

dc.contributor.author	Ekşi, Z.
dc.contributor.author	Özcan, M.E.
dc.contributor.author	Çakıroğlu, M.
dc.contributor.author	Öz, C.
dc.contributor.author	Aralaşmak, A.
dc.date.accessioned	2021-12-21T08:40:30Z
dc.date.available	2021-12-21T08:40:30Z
dc.date.issued	2021
dc.identifier.issn	15901874
dc.identifier.uri	https://doi.org/10.1007/s10072-020-04950-0
dc.identifier.uri	http://dspace.yeniyuzyil.edu.tr:8080/xmlui/handle/20.500.12629/1020
dc.description.abstract	Some multiple sclerosis (MS) lesions may have great similarities with neoplastic brain lesions in magnetic resonance (MR) imaging and thus wrong diagnoses may occur. In this study, differentiation of MS and low-grade brain tumors was performed with comput
dc.description.sponsorship	This study was supported by Sakarya University BAPK (Project No: 2015-50-02-012). The authors wish to thank all patients included in the study for their approval to the use of their MRS data for research and educational purposes.
dc.language.iso	English
dc.publisher	Springer-Verlag Italia s.r.l.
dc.title	Differentiation of multiple sclerosis lesions and low-grade brain tumors on MRS data: machine learning approaches
dc.type	Article
dc.relation.journal	Neurological Sciences
dc.identifier.issue	8
dc.identifier.startpage	3389
dc.identifier.endpage	3395
dc.identifier.volume	42
dc.identifier.doi	10.1007/s10072-020-04950-0
dc.relation.issue	8
dc.relation.volume	42

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