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

dc.contributor.author	Eksi, Ziya
dc.contributor.author	Ozcan, Muhammed Emin
dc.contributor.author	cakiroglu, Murat
dc.contributor.author	Oz, Cemil
dc.contributor.author	Aralasmak, Ayse
dc.date.accessioned	2021-12-21T08:46:38Z
dc.date.available	2021-12-21T08:46:38Z
dc.date.issued	2021
dc.identifier.issn	1590-1874
dc.identifier.issn	1590-3478
dc.identifier.uri	https://doi.org/10.1007/s10072-020-04950-0
dc.identifier.uri	http://dspace.yeniyuzyil.edu.tr:8080/xmlui/handle/20.500.12629/2059
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	Sakarya University BAPKSakarya University [2015-50-02-012]
dc.language.iso	English
dc.publisher	Sprınger-Verlag Italıa Srl
dc.title	Differentiation of multiple sclerosis lesions and low-grade brain tumors on MRS data: machine learning approaches
dc.type	Article
dc.relation.journal	Neurologıcal Scıences
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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