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On the generalizabi...
On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types : Chronicles of the MEMENTO challenge
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- De Luca, Alberto (författare)
- Univ Med Ctr Utrecht, Netherlands; Univ Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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- Ianus, Andrada (författare)
- Champalimaud Ctr Unknown, Portugal
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- Leemans, Alexander (författare)
- Univ Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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- Palombo, Marco (författare)
- UCL, England,University College London
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- Shemesh, Noam (författare)
- Champalimaud Ctr Unknown, Portugal
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- Zhang, Hui (författare)
- UCL, England,University College London
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- Alexander, Daniel C. (författare)
- UCL, England,University College London
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- Nilsson, Markus (författare)
- Lund University,Lunds universitet,Diagnostisk radiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Diagnostic Radiology, (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LUCC: Lund University Cancer Centre,Other Strong Research Environments
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- Froeling, Martijn (författare)
- Univ Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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- Biessels, Geert-Jan (författare)
- Univ Med Ctr Utrecht, Netherlands,University Medical Center Utrecht
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- Zucchelli, Mauro (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Frigo, Matteo (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Albay, Enes (författare)
- Univ Cote dAzur, France; Istanbul Tech Univ, Turkey,University of Côte d'Azur,Istanbul Technical University
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- Sedlar, Sara (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Alimi, Abib (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Deslauriers-Gauthier, Samuel (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Deriche, Rachid (författare)
- Univ Cote dAzur, France,University of Côte d'Azur
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- Fick, Rutger (författare)
- TRIBVN Healthcare, France
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- Afzali, Maryam (författare)
- Cardiff Univ, Wales
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- Pieciak, Tomasz (författare)
- AGH Univ Sci & Technol, Poland; Univ Valladolid, Spain,University of Valladolid,AGH University of Science and Technology
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- Bogusz, Fabian (författare)
- AGH Univ Sci & Technol, Poland,AGH University of Science and Technology
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- Aja-Fernandez, Santiago (författare)
- Univ Valladolid, Spain,University of Valladolid
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- Özarslan, Evren (författare)
- Linköping University,Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Jones, Derek K. (författare)
- Cardiff Univ, Wales
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- Chen, Haoze (författare)
- North Univ China, Peoples R China
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- Jin, Mingwu (författare)
- Univ Texas Arlington, TX 76019 USA,University of Texas at Arlington
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- Zhang, Zhijie (författare)
- North Univ China, Peoples R China
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- Wang, Fengxiang (författare)
- North Univ China, Peoples R China
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- Nath, Vishwesh (författare)
- NVIDIA Corp, MD USA
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- Parvathaneni, Prasanna (författare)
- NIH, MD 20892 USA,National Institutes of Health, United States
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- Morez, Jan (författare)
- Univ Antwerp, Belgium,University of Antwerp
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- Sijbers, Jan (författare)
- Univ Antwerp, Belgium,University of Antwerp
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- Jeurissen, Ben (författare)
- Univ Antwerp, Belgium,University of Antwerp
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- Fadnavis, Shreyas (författare)
- Indiana Univ, IN 47405 USA,Indiana University
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- Endres, Stefan (författare)
- Univ Bremen, Germany,University of Bremen
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- Rokem, Ariel (författare)
- Univ Washington, WA 98195 USA; Univ Washington, WA 98195 USA,University of Washington
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- Garyfallidis, Eleftherios (författare)
- Indiana Univ, IN 47405 USA,Indiana University
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- Sanchez, Irina (författare)
- QMENTA Inc, MA USA
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- Prchkovska, Vesna (författare)
- QMENTA Inc, MA USA
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- Rodrigues, Paulo (författare)
- QMENTA Inc, MA USA
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- Landman, Bennet A. (författare)
- Vanderbilt Univ, TN 37235 USA
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- Schilling, Kurt G. (författare)
- Vanderbilt Univ, TN 37235 USA; Vanderbilt Univ, TN 37232 USA,Vanderbilt University
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(creator_code:org_t)
- Elsevier BV, 2021
- 2021
- Engelska.
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Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 240
- Relaterad länk:
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https://liu.diva-por... (primary) (Raw object)
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https://doi.org/10.1...
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http://dx.doi.org/10... (free)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://lup.lub.lu.s...
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Abstract
Ämnesord
Stäng
- Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the last two decades, several signal representations have been proposed to fit the dMRI signal and decode such properties. Most methods, however, are tested and developed on a limited amount of data, and their applicability to other acquisition schemes remains unknown. With this work, we aimed to shed light on the generalizability of existing dMRI signal representations to different diffusion encoding parameters and brain tissue types. To this end, we organized a community challenge - named MEMENTO, making available the same datasets for fair comparisons across algorithms and techniques. We considered two state-of-the-art diffusion datasets, including single-diffusion-encoding (SDE) spin-echo data from a human brain with over 3820 unique diffusion weightings (the MASSIVE dataset), and double (oscillating) diffusion encoding data (DDE/DODE) of a mouse brain including over 2520 unique data points. A subset of the data sampled in 5 different voxels was openly distributed, and the challenge participants were asked to predict the remaining part of the data. After one year, eight participant teams submitted a total of 80 signal fits. For each submission, we evaluated the mean squared error, the variance of the prediction error and the Bayesian information criteria. The received submissions predicted either multi-shell SDE data (37%) or DODE data (22%), followed by cartesian SDE data (19%) and DDE (18%). Most submissions predicted the signals measured with SDE remarkably well, with the exception of low and very strong diffusion weightings. The prediction of DDE and DODE data seemed more challenging, likely because none of the submissions explicitly accounted for diffusion time and frequency. Next to the choice of the model, decisions on fit procedure and hyperparameters play a major role in the prediction performance, highlighting the importance of optimizing and reporting such choices. This work is a community effort to highlight strength and limitations of the field at representing dMRI acquired with trending encoding schemes, gaining insights into how different models generalize to different tissue types and fiber configurations over a large range of diffusion encodings.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
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- ref (ämneskategori)
- art (ämneskategori)
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Till lärosätets databas
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De Luca, Alberto
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Ianus, Andrada
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Leemans, Alexand ...
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Palombo, Marco
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Shemesh, Noam
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Zhang, Hui
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visa fler...
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Alexander, Danie ...
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Nilsson, Markus
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Froeling, Martij ...
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Biessels, Geert- ...
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Zucchelli, Mauro
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Frigo, Matteo
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Albay, Enes
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Sedlar, Sara
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Alimi, Abib
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Deslauriers-Gaut ...
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Deriche, Rachid
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Fick, Rutger
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Afzali, Maryam
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Pieciak, Tomasz
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Bogusz, Fabian
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Aja-Fernandez, S ...
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Özarslan, Evren
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Jones, Derek K.
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Chen, Haoze
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Jin, Mingwu
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Zhang, Zhijie
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Wang, Fengxiang
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Nath, Vishwesh
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Parvathaneni, Pr ...
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Morez, Jan
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Sijbers, Jan
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Jeurissen, Ben
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Fadnavis, Shreya ...
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Endres, Stefan
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Rokem, Ariel
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Garyfallidis, El ...
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Sanchez, Irina
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Prchkovska, Vesn ...
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Rodrigues, Paulo
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Landman, Bennet ...
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Schilling, Kurt ...
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- Om ämnet
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- NATURVETENSKAP
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NATURVETENSKAP
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och Data och informa ...
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och Bioinformatik
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Radiologi och bi ...
- Artiklar i publikationen
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NeuroImage
- Av lärosätet
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Linköpings universitet
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Lunds universitet