ArticleJournal of magnetic resonance imaging : JMRI2014
White matter segmentation based on a skeletonized atlas: effects on diffusion tensor imaging studies of regions of interest.
Article in Journal of magnetic resonance imaging : JMRI, 2014. 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.
- From images to insights: a neuroradiologist's practical guide on white matter fiber tract anatomy and DTI patterns for pre-surgical planning.Neuroradiology · 2024Review
- Brain volumes and white matter microstructure in 8- to 10-year-old children born with fetal growth restriction.Pediatric radiology · 2022Article
- Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means.NeuroImage · 2021Article
- White matter microstructure disruption in early stage amyloid pathology.Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
- Article
- A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging.NeuroImage · 2017Article
- Declines in inflammation predict greater white matter microstructure in older adults.Neurobiology of aging · 2015Article
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Abstract
purposeTo compare the influence of conventional and skeletonized atlas-based white matter (WM) segmentation on diffusion tensor imaging (DTI) region-of-interest (ROI) investigations. MATERIALS AND
methodsA conventional WM atlas was skeletonized by thinning the corresponding fractional anisotropy (FA) map and labels. The conventional and skeletonized versions of the atlas were used for WM segmentation. The percentage of non-WM voxels assigned to WM labels, as well as statistical summaries of tensor-derived quantities, were compared between segmentation approaches. The ability to detect small differences in diffusion properties across groups of subjects was also compared between segmentation approaches.
resultsSkeletonized segmentation resulted in significantly lower non-WM percentage (P < 0.05), higher mean FA and lower trace (P < 0.05) in most WM labels, and mainly lower standard deviation of FA and trace in labels neighboring the ventricles. In terms of maximizing the ability to detect intergroup DTI differences, skeletonized segmentation was superior in the corpus callosum, but the optimal approach varied for other WM labels.
conclusionConventional and skeletonized atlas-based segmentation probe different portions of brain tissue and lead to different statistical summaries of diffusion characteristics in WM labels. Careful selection of segmentation approach is required for DTI investigations of WM ROIs.
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