In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging
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...
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| Published in | Scientific data Vol. 5; no. 1; pp. 180270 - 11 |
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| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
27.11.2018
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Summary: | 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.
Design Type(s)
anatomical image analysis objective • data collection and processing objective
Measurement Type(s)
regional part of brain
Technology Type(s)
digital curation
Factor Type(s)
Sample Characteristic(s)
Homo sapiens • thalamus
Machine-accessible metadata file describing the reported data
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23 These authors contributed equally to this work. E.N. co-designed the study, co-programmed and applied the thalamic clustering method on both HCP and testing dataset, was involved in the technical-validation analysis, and co-wrote the manuscript with contributions from all other authors. Y.A.G. co-designed the study, programmed the creation of the custom template and the probabilistic atlas, performed the comparative analysis for the technical validation, and co-wrote the manuscript with contributions from all authors. G.B. gave advices on the study design, co-programmed and co-performed the thalamic clustering in the testing dataset, and contributed to the manuscript. M.D. analyzed the HCP data (image registration), was involved in the atlas-construction design, and contributed to the manuscript. P.H. participated in the design of the atlas and revised the manuscript. S.J. was involved in the assemble of the dataset used for the technical validation. P.M. visually evaluated and interpreted the cluster-based thalamic parcellation in each subject of the testing dataset, and revised the manuscript. J.-P.T. gave conceptual advises for the analysis of the DW-MRI data and revised the manuscript. E.F. co-designed the study and revised the manuscript. M.B.C. co-designed the study, was involved in the interpretation and the discussions regarding the implication of the output data, and contributed to the manuscript. |
| ISSN: | 2052-4463 2052-4463 |
| DOI: | 10.1038/sdata.2018.270 |