ArticleData in brief2024
High-resolution dataset of manual claustrum segmentation.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multiscale characterization of the human claustrum from histology to MRI.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The Human Visual Claustrum Responses to Physical Stimulus Properties and Subjective Content During Movie Viewing.Human brain mapping · 2026Article
- A Contrast-Agnostic Method for Ultra-High Resolution Claustrum Segmentation.Human brain mapping · 2025Article
- A comprehensive and reliable protocol for manual segmentation of the human claustrum using high-resolution MRI.Brain structure & function · 2025Article
- High-resolution 7T fMRI reveals the visual zone of the human claustrum.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The claustrum has a unique thin sheet-like structure that makes it hard to identify in typical anatomical MRI scans. Attempts have been made to identify the claustrum in anatomical images with either automatic segmentation techniques or using atlas-based approaches. However, the resulting labels fail to include the ventral claustrum portion, which consists of fragmented grey matter referred to as "puddles". The current dataset is a high-resolution label of the whole claustrum manually defined using an ultra-high resolution postmortem MRI image of one individual. Manual labelling was performed by four independent research trainees. Two trainees labelled the left claustrum and another two trainees labelled the right claustrum. For every hemisphere we created a union of the two labels and assessed the label correspondence using dice coefficients. We provide size measurements of the labels in MNI space by calculating the oriented bounding box size. These data are the first manual claustrum segmentation labels that include both the dorsal and ventral claustrum regions at such a high resolution in standard space. The label can be used to approximate the claustrum location in typical in vivo MRI scans of healthy individuals.
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