ArticleMagnetic resonance in medicine2021
Optimized rectification of fiber orientation density function.
Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Intra-voxel angular dispersion of fibers in corpus callosum decreases with healthy aging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Optimized rectification of fiber orientation density function with background threshold.Magnetic resonance imaging · 2023Article
- High b-value diffusion tractography: Abnormal axonal network organization associated with medication-refractory epilepsy.NeuroImage · 2022Article
- High fidelity fiber orientation density functions from fiber ball imaging.NMR in biomedicine · 2022Article
- Associations of White Matter and Basal Ganglia Microstructure to Cognitive Fatigue Rate in Multiple Sclerosis.Frontiers in neurology · 2022Article
- Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project.Frontiers in human neuroscience · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
purposeTo demonstrate an optimized rectification strategy for fiber orientation density functions (fODFs). THEORY AND
methodsIn white matter, fODFs can be estimated with diffusion MRI. However, because of signal noise, imaging artifacts and other factors, experimentally determined fODFs may take on unphysical negative values in some directions. Here, we show how to rectify such fODFs to eliminate all negative values while minimizing the mean square difference between the original and rectified fODFs. The method is demonstrated for a mathematical model and for fODFs estimated from experimental human data using both constrained spherical deconvolution and fiber ball imaging. Comparison with an alternative nonoptimized rectification approach is also provided.
resultsFor the mathematical model, it is found that the optimized rectification procedure removes negative fODF values while at the same time reducing the mean square error. Relative to the alternative rectification approach, the optimized fODFs are substantially more accurate. For the experimental data, the optimized fODFs have a lower average fractional anisotropy axonal and often fewer small peaks than the original, unrectified fODFs. The calculation of optimized fODFs is straightforward where the main step is the finding of the root to an equation in one variable, as may be efficiently accomplished with the bisection method.
conclusionUnphysical negative fODF values can be easily eliminated in a manner that minimizes the mean square difference between the original and rectified fODFs. Optimized fODF rectification may be useful in applications for which negative values are problematic.
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