In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging.
Fiche du document
27 novembre 2018
- doi: 10.1038/sdata.2018.270
- issn: 2052-4463
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1038/sdata.2018.270
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/30480664
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/2052-4463
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_F5359B7953904
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
Sujets proches
Scientific atlases Optic thalamus World geographic atlases Atlases, American Geographical atlases American atlases Geographic atlases World atlases Geography--Atlases Diffusion-weighted imaging Diffusion-weighted magnetic resonance imagingCiter ce document
E. Najdenovska et al., « In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging. », Serveur académique Lausannois, ID : 10.1038/sdata.2018.270
Métriques
Partage / Export
Résumé
The thalamic nuclei are involved in many neurodegenerative diseases and therefore, their identification is of key importance in numerous clinical treatments. Automated segmentation of thalamic subparts is currently achieved by exploring diffusion-weighted magnetic resonance imaging (DW-MRI), but in absence of such data, atlas-based segmentation can be used as an alternative. Currently, there is a limited number of available digital atlases of the thalamus. Moreover, all atlases are created using a few subjects only, thus are prone to errors due to the inter-subject variability of the thalamic morphology. In this work, we present a probabilistic atlas of anatomical subparts of the thalamus built upon a relatively large dataset where the individual thalamic parcellation was done by employing a recently proposed automatic diffusion-based clustering method. Our analyses, comparing the segmentation performance between the atlas-based and the clustering method, demonstrate the ability of the provided atlas to substitute the automated diffusion-based subdivision in the individual space when the DW-MRI is not available.