ArticleBrain structure & function2022
Manual delineation approaches for direct imaging of the subcortex.
Article in Brain structure & function, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 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
- Feasibility of Non-Sedate Magnetic Resonance Imaging for Children with Cerebral Palsy: Tolerance and Structural Analysis Considerations.Children (Basel, Switzerland) · 2026Article
- Neuroanatomical Changes in the Stopping Network Across the Adult Lifespan Assessed With Quantitative and Diffusion MRI.Human brain mapping · 2025Article
- A road map to manual segmentation of cerebral structures.Journal of anatomy · 2025Review
- Abnormalities of iron homeostasis and the dopaminergic system in Tourette syndrome revealed by 7T MRI and PET.Brain communications · 2025Article
- Automated parcellation and atlasing of the human subcortex with ultra-high resolution quantitative MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
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Authors and funding
4 authors.
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Abstract
The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.
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Registered trials
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