ArticlePloS one2018
A scalable method to improve gray matter segmentation at ultra high field MRI.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Bridging the gap with invasive imaging: promises and challenges of a new generation of ultrahigh resolution fMRI.bioRxiv : the preprint server for biology · 2026Article
- T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data.Magnetic resonance in medicine · 2025Article
- Larger brains and relatively smaller cerebella in Asian elephants compared with African savanna elephants.PNAS nexus · 2025Article
- A lifespan-generalizable skull-stripping model for magnetic resonance images that leverages prior knowledge from brain atlases.Nature biomedical engineering · 2025Article
- T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data.bioRxiv : the preprint server for biology · 2024Article
- Insights into hippocampal perfusion using high-resolution, multi-modal 7T MRI.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024Article
- Systematic cortical thickness and curvature patterns in primates.NeuroImage · 2023Article
- Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Combining arterial blood contrast with BOLD increases fMRI intracortical contrast.Human brain mapping · 2023Article
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- CEREBRUM-7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes.Human brain mapping · 2021Article
- LayNii: A software suite for layer-fMRI.NeuroImage · 2021Article
- Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: effects on signal strength.Neurophotonics · 2021Article
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- Mapping the human subcortical auditory system using histology, postmortem MRI and in vivo MRI at 7T.eLife · 2019Article
- The impact of B1+ correction on MP2RAGE cortical THuman brain mapping · 2018Article
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Authors and funding
5 authors.
Funding
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Abstract
High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.
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