Evidence map›Paper›PMID 32710476›Full record

ArticleMagnetic resonance in medicine2021

Optimized rectification of fiber orientation density function.

Hunter G Moss, Jens H Jensen

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hunter G MossCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA.
Jens H JensenCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA.ORCID 0000-0003-3219-4287

Funding

TRAINING PROGRAM FOR MEDICAL SCIENTISTST32GM008716 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DEMORE, NANCY · 1999 to 2024
$9.3M
Quantitative Neuroimaging Assessment of White Matter Integrity in the Context of Aging and ADR01AG054159 · NIA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Andreana Benitez · 2017 to 2026
$8.9M
Advanced Diffusion MRI Applied in Hypoxic-ischemic NeonatesF31NS108623 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI MOSS, HUNTER · 2019 to 2021
$123k
NIGMS NIH HHS T32 GM008716NINDS NIH HHS F31 NS108623
6 · The paper itself

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.

Indexed as

Image Processing, Computer-AssistedWhite MatterAnisotropyAxonsBrainDiffusion Magnetic Resonance ImagingHumansaxonconstrained spherical deconvolutionfiber ball imagingfiber orientation density functionrectificationwhite matter

Identifiers

PMID32710476
PMCPMC8007078

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.