Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem
Grantová podpora
U54 AI117924
NIAID NIH HHS - United States
R01 AG037639
NIA NIH HHS - United States
R01 AI138647
NIAID NIH HHS - United States
R01 MH125479
NIMH NIH HHS - United States
R01 EB028774
NIBIB NIH HHS - United States
P50 HD105353
NICHD NIH HHS - United States
R01 NS102665
NINDS NIH HHS - United States
UF1 AG051216
NIA NIH HHS - United States
U54 HD090256
NICHD NIH HHS - United States
P50 AG033514
NIA NIH HHS - United States
P41 EB017183
NIBIB NIH HHS - United States
R01 NS092870
NINDS NIH HHS - United States
R34 DA050258
NIDA NIH HHS - United States
R01 EB017230
NIBIB NIH HHS - United States
R01 NS117568
NINDS NIH HHS - United States
R01 NS124920
NINDS NIH HHS - United States
R01 NS111022
NINDS NIH HHS - United States
P30 AG066512
NIA NIH HHS - United States
K01 EB032898
NIBIB NIH HHS - United States
R01 EB022883
NIBIB NIH HHS - United States
R01 AG027161
NIA NIH HHS - United States
P01 AI132132
NIAID NIH HHS - United States
RF1 AG059312
NIA NIH HHS - United States
R01 NS123378
NINDS NIH HHS - United States
R01 NS105646
NINDS NIH HHS - United States
R21 NS126806
NINDS NIH HHS - United States
R01 NS082436
NINDS NIH HHS - United States
PubMed
37330025
PubMed Central
PMC10771037
DOI
10.1016/j.neuroimage.2023.120231
PII: S1053-8119(23)00382-8
Knihovny.cz E-zdroje
- Klíčová slova
- Challenge, Connectivity, Diffusion MRI, Microstructure, Monte carlo simulation, Numerical substrates, Tractography,
- MeSH
- difuzní magnetická rezonance * metody MeSH
- fantomy radiodiagnostické MeSH
- lidé MeSH
- metoda Monte Carlo MeSH
- mozek diagnostické zobrazování MeSH
- počítačové zpracování obrazu * metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.
AGH University of Science and Technology Kraków Poland
Athena Project Team Centre Inria d'Université Côte d'Azur France
Computer Science Department Centro de Investigación en Matemáticas A C Guanajuato México
Department of Electrical and Computer Engineering Vanderbilt University Nashville TN United States
Department of Medicine University of Wisconsin Madison Madison WI United States
Department of Radiology Stanford University Stanford CA United States
Department of Radiology University of Wisconsin Madison Madison WI United States
Instituto de Neurobiología Universidad Nacional Autónoma de México Juriquilla Querétaro México
Sano Centre for Computational Personalised Medicine Kraków Poland
Signal Processing Laboratory Lausanne Switzerland
Signal Processing Laboratory Lausanne Switzerland; McGill University Montréal QC Canada
Univ Rennes Inria CNRS Inserm IRISA UMR 6074 Empenn ERL U 1228 Rennes France
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