ArticleJournal of neuroscience methods2016
Methodology for computing white matter nerve fiber orientation in human histological slices.
Article in Journal of neuroscience methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- NEUSEG: INTERPRETABLE UNSUPERVISED GM/WM SEGMENTATION IN BRAIN HISTOPATHOLOGY USING NUCLEI MORPHOMETRICS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2026Article
- Design and validation of diffusion MRI models of white matter.Frontiers in physics · 2017Article
- Quantitative validation of a nonlinear histology-MRI coregistration method using generalized Q-sampling imaging in complex human cortical white matter.NeuroImage · 2017Article
- Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study.PloS one · 2017Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe gold standard for mapping nerve fiber orientation in white matter of the human brain is histological analysis through biopsy. Such mappings are a crucial step in validating non-invasive techniques for assessing nerve fiber orientation in the human brain by using diffusion MRI. However, the manual extraction of nerve fiber directions of histological slices is tedious, time consuming, and prone to human error. NEW
methodThe presented semi-automated algorithm first creates a binary-segmented mask of the nerve fibers in the histological image, and then extracts an estimate of average directionality of nerve fibers through a Fourier-domain analysis of the masked image. It also generates an uncertainty level for its estimate of average directionality. RESULTS AND COMPARISON WITH EXISTING
methodsThe average orientations of the semi-automatic method were first compared to a qualitative expert opinion based on visual inspection of nerve fibers. A weighted RMS difference between the expert estimate and the algorithmically determined angle (weighted by expert's confidence in his estimate) was 15.4°, dropping to 9.9° when only cases with an expert confidence level of greater than 50% were included. The algorithmically determined angles were then compared with angles extracted using a manual segmentation technique, yielding an RMS difference of 11.2°.
conclusionThe presented semi-automated method is in good agreement with both qualitative and quantitative manual expert-based approaches for estimating directionality of nerve fibers in white matter from images of stained histological slices of the human brain.
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