High-resolution dataset of manual claustrum segmentation

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 includes 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.

Annotations for: High-resolution dataset of manual claustrum segmentation

✅ Key Points

Claustrum structure [@coatesHighresolutionDatasetManual2024, p. 1]

The claustrum has a unique thin sheet-like structure that makes it hard to identify in typical anatomical MRI scans. [@coatesHighresolutionDatasetManual2024, p. 1]

Current work [@coatesHighresolutionDatasetManual2024, p. 1]

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. [@coatesHighresolutionDatasetManual2024, p. 1]

This is a test [@coatesHighresolutionDatasetManual2024, p. 1]
Rationale [@coatesHighresolutionDatasetManual2024, p. 2]

human claustrum is difficult to identify in standard structural MRI scans due to its thin and fragmented shape. [@coatesHighresolutionDatasetManual2024, p. 2]

The labels can be subsequently used to extract functional, diffusion or any other MRI parameters specific to the claustrum region. and as a seed for functional and structural connectivity studies of the claustrum. [@coatesHighresolutionDatasetManual2024, p. 2]

Background [@coatesHighresolutionDatasetManual2024, p. 2]

The human claustrum is a sheet-like bilateral subcortical brain structure, whose functional role is poorly understood. [@coatesHighresolutionDatasetManual2024, p. 2]

test woohoo [@coatesHighresolutionDatasetManual2024, p. 4]
Methods used. Ultra high resolution fMRI - to be able to see claustrum [@coatesHighresolutionDatasetManual2024, p. 5]

The anatomical location of the claustrum was identified in an ultra-high resolution (0.1 mm3 voxel size) anatomical postmortem MRI image of an individual 58-year-old female [@coatesHighresolutionDatasetManual2024, p. 5]

ultra-high resolution anatomical scan as background. [@coatesHighresolutionDatasetManual2024, p. 5]

test woohoo [@coatesHighresolutionDatasetManual2024, p. 5]

Background

empts have been made to iden [@coatesHighresolutionDatasetManual2024, p. 1]

Hypothesis

he claustrum in anato [@coatesHighresolutionDatasetManual2024, p. 1]

Methods

cal images [@coatesHighresolutionDatasetManual2024, p. 1]

Results

with e [@coatesHighresolutionDatasetManual2024, p. 1]

Conclusions

utoma [@coatesHighresolutionDatasetManual2024, p. 1]

Implications

egmentation [@coatesHighresolutionDatasetManual2024, p. 1]

number of slices per clausturm [@coatesHighresolutionDatasetManual2024, p. 5]

1st label = 544 and for the 2nd label = 593, right number of slices for the 1st label = 481 and for the 2nd label = 473 [@coatesHighresolutionDatasetManual2024, p. 5]

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