Evidence map›Paper›PMID 34296223›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2018

A Multi-Tissue Global Estimation Framework for Asymmetric Fiber Orientation Distributions.

Ye Wu, Yuanjing Feng, Dinggang Shen, Pew-Thian Yap

Abstract read
In one paragraph

Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018. 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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.

  1. Imaging of the superficial white matter in health and disease.Imaging neuroscience (Cambridge, Mass.) · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Asymmetry Spectrum Imaging for Baby Diffusion Tractography.Information processing in medical imaging : proceedings of the ... conference · 2019
    Article
  6. Active Cortex Tractography.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
    Article
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

4 authors.

Ye WuInstitute of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China.
Yuanjing FengInstitute of Information Processing and Automation, Zhejiang University of Technology, Hangzhou, China.
Dinggang ShenDepartment of Radiology and BRIC, University of North Carolina, Chapel Hill, USA.
Pew-Thian YapDepartment of Radiology and BRIC, University of North Carolina, Chapel Hill, USA.

Funding

NEUROIMAGING OF CONNECTIVITY IN ALCOHOLISMR01AA012388 · NIAAA · SRI INTERNATIONAL · PI PFEFFERBAUM, ADOLF, SULLIVAN, EDITH VIONI · 2000 to 2015
$10.6M
Development of Robust Brain Measurement Tools Informed by Ultrahigh Field 7T MRIR01EB006733 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YAP, PEW-THIAN · 2008 to 2020
$4.5M
Quantifying Brain Abnormality by Multimodality Neuroimage Analysis,R01AG041721 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIU, MINGXIA · 2012 to 2019
$3.0M
Infant Brain Measurement and Super-Resolution Atlas ConstructionR01MH100217 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHEN, DINGGANG · 2013 to 2016
$2.3M
Fast, Robust Analysis of Large Population DataR01EB009634 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHEN, DINGGANG · 2011 to 2014
$1.3M
Diagnosis of Alzheimer's Disease Using Dynamic High-Order Brain NetworksR01EB022880 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YAP, PEW-THIAN · 2016 to 2018
$1.1M
Robust White Matter Morphometry with Small DatabasesR01NS093842 · NINDS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YAP, PEW-THIAN · 2016 to 2018
$1.1M
NIAAA NIH HHS R01 AA012388NIA NIH HHS R01 AG041721NIBIB NIH HHS R01 EB006733NIBIB NIH HHS R01 EB009634NIBIB NIH HHS R01 EB022880NIMH NIH HHS R01 MH100217NINDS NIH HHS R01 NS093842
6 · The paper itself

Abstract

In connectomics, tractography involves tracing connections across gray-white matter boundaries in gyral blades of complex cortical convolutions. To date, most tractography algorithms exhibit gyral bias with fiber streamlines preferentially terminating at gyral crowns rather than sulcal banks or fundi. In this work, we will demonstrate that a multi-tissue global estimation framework of the asymmetric fiber orientation distribution function (AFODF) will mitigate the effects of gyral bias and will allow fiber streamlines at gyral blades to make sharper turns into the cortical gray matter. This is validated using in-vivo data from the Human Connectome Project (HCP), showing that, in a typical gyral blade with high curvature, the fiber streamlines estimated using AFODFs bend more naturally into the cortex than FODFs. Furthermore, we show that AFODF tractography results in better cortico-cortical connectivity.

Identifiers

PMID34296223
PMCPMC8294669

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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.