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Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four a...

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four a...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7674567

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort

About this item

Full title

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

Journal title

Journal of neurology, 2020-12, Vol.267 (12), p.3541-3554

Language

English

Formats

Publication information

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

More information

Scope and Contents

Contents

Background
Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesi...

Alternative Titles

Full title

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7674567

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7674567

Other Identifiers

ISSN

0340-5354

E-ISSN

1432-1459

DOI

10.1007/s00415-020-10023-1

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