Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T20:33:42.664381Z
Paper Citation Record · LEDGER
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI
As of 22 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.09618.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
47 of 47 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0dd94ebf-7a5c-4649-ba1d-b37069d28f4d · outbound
This paper cites URL https://naccdata.org/.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI URL https://naccdata.org/
Reference 1
- Resolution
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This paper cites URL https://github.com/scilus/scilpy.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI URL https://github.com/scilus/scilpy
Reference 2
- Resolution
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This paper cites A classification of hand preference by association analysis.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI A classification of hand preference by association analysis
Reference 3
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This paper cites Basser, James Mattiello, and Denis Lebihan.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Basser, James Mattiello, and Denis Lebihan
Reference 4
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This paper cites pnlbwh/dmriharmonization: Multi-site dmri harmonization.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI pnlbwh/dmriharmonization: Multi-site dmri harmonization
Reference 5
- Resolution
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Observation 14c9ae91-cf58-4469-8b1b-ed64f5e19035 · outbound
This paper cites Cai, Qi Yang, Colin B.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Cai, Qi Yang, Colin B
Reference 6
- Resolution
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Observation 64a0ad28-8219-4dd9-bc4f-9a08acff5b40 · outbound
This paper cites Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations
Reference 7
- Resolution
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This paper cites Statistical power analysis for the behavioral sciences second edition.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Statistical power analysis for the behavioral sciences second edition
Reference 8
- Resolution
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This paper cites an unresolved cited work.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Unresolved cited work
Reference 9
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Observation e5edd0c2-043e-4a69-ae1f-e7bce4af60a7 · outbound
This paper cites Dewey, Can Zhao, Jacob C.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Dewey, Can Zhao, Jacob C
Reference 10
- Resolution
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Source-reported events for the cited work
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Observation eeb21839-aa21-4956-a210-cc7833dd9295 · outbound
This paper cites The baltimore longitudinal study of aging (blsa): A 50-year-long journey and plans for the future.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI The baltimore longitudinal study of aging (blsa): A 50-year-long journey and plans for the future
Reference 11
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Observation 7dbbfbe5-a38e-427b-8786-ad4048a5db4e · outbound
This paper cites Freesurfer.
Reference 12
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This paper cites Optimal and algorithmic norm regularization of random matrices.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Optimal and algorithmic norm regularization of random matrices
Reference 13
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Observation 654e44a7-46f9-46a1-9c69-7e1f053bdb77 · outbound
This paper cites Dipy, a library for the analysis of diffusion mri data.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Dipy, a library for the analysis of diffusion mri data
Reference 14
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This paper cites Recognition of white matter bundles using local and global streamline-based registration and clustering.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Recognition of white matter bundles using local and global streamline-based registration and clustering
Reference 15
- Resolution
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Observation 9b1c23ec-0add-430b-b901-0d0183e40631 · outbound
This paper cites Greve and Bruce Fischl.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Greve and Bruce Fischl
Reference 16
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Observation 9650f508-6e7a-4c28-940d-e578090456ee · outbound
This paper cites Hansen, Kurt G.
Reference 17
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Observation 780f75d3-3aa6-41f2-b5da-a1bd753a4a7c · outbound
This paper cites Neural spherical harmonics for structurally coherent continuous representation of diffusion mri signal.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Neural spherical harmonics for structurally coherent continuous representation of diffusion mri signal
Reference 18
- Resolution
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This paper cites Chen, Hannah Horng, Vishnu Bashyam, Christos Davatzikos, Aaron Alexander-Bloch, Mingyao Li, Haochang Shou, Theodore D.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Chen, Hannah Horng, Vishnu Bashyam, Christos Davatzikos, Aaron Alexander-Bloch, Mingyao Li, Haochang Shou, Theodore D
Reference 19
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Reference 20
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This paper cites Beckmann, Timothy E.J.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Beckmann, Timothy E.J
Reference 21
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This paper cites Retrospective harmonization of multi-site diffusion mri data acquired with different acquisition parameters.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Retrospective harmonization of multi-site diffusion mri data acquired with different acquisition parameters
Reference 22
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This paper cites A style-based generator architecture for generative adversarial networks, 2019.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI A style-based generator architecture for generative adversarial networks, 2019
Reference 23
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Observation 2c74d688-f0d6-4350-abdd-2428cc043c7f · outbound
This paper cites Constraints on the rate of supernovae lasting for more than a year from Subaru/Hyper Suprime-Cam.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Constraints on the rate of supernovae lasting for more than a year from Subaru/Hyper Suprime-Cam
Reference 24
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI LaMontagne, Tammie LS
Reference 25
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Marx, Rajendra A
Reference 26
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Nencka, Timothy B
Reference 27
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This paper cites Newlin, François Rheault, Kurt G.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Newlin, François Rheault, Kurt G
Reference 28
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Unresolved cited work
Reference 29
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This paper cites Blumberg, Can Son Khoo, Marco Palombo, Jaume Coll-Font, Benoit Scherrer, Simon K.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Blumberg, Can Son Khoo, Marco Palombo, Jaume Coll-Font, Benoit Scherrer, Simon K
Reference 30
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Blumberg, Can Son Khoo, Marco Palombo, Iasonas Kokkinos, Daniel C
Reference 31
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Onicas, Ashley L
Reference 32
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Basser, Alan Barnett, and Giovanni Di Chiro
Reference 33
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI den Dekker, and Jan Sijbers
Reference 34
- Resolution
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Super-resolution of multi dimensional diffusion mri data
Reference 35
- Resolution
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Complex network measures of brain connectivity: uses and interpretations
Reference 36
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Schilling, Chantal M.W
Reference 37
- Resolution
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This paper cites Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient
Reference 38
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Strike, Gabriella A.M
Reference 39
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Donald Tournier, Fernando Calamante, and Alan Connelly
Reference 40
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Unavailable: canonical work link unavailable.
Observation ab9a1c1f-8b8e-4dd6-8ffb-abb19e41ebfc · outbound
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Donald Tournier, Fernando Calamante, and Alan Connelly
Reference 41
- Resolution
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Observation 188ffd21-9cc1-485b-b6fe-6c53012679c6 · outbound
This paper cites Donald Tournier, Robert Smith, David Raffelt, Rami Tabbara, Thijs Dhollander, Maximilian Pietsch, Daan Christiaens, Ben Jeurissen, Chun Hung Yeh, and Alan Connelly.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Donald Tournier, Robert Smith, David Raffelt, Rami Tabbara, Thijs Dhollander, Maximilian Pietsch, Daan Christiaens, Ben Jeurissen, Chun Hung Yeh, and Alan Connelly
Reference 42
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Unavailable: canonical work link unavailable.
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Reference 43
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Unresolved cited work
Reference 44
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Observation f0fc1cbb-af7c-4a69-886e-eb914921491b · outbound
This paper cites Landman, Matthias Eisenmann, Laura Aguilera Saiz, M.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Landman, Matthias Eisenmann, Laura Aguilera Saiz, M
Reference 45
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Unavailable: canonical work link unavailable.
Observation 27ecfb92-69f4-47bc-9ec3-190a3b6afa06 · outbound
This paper cites an unresolved cited work.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Unresolved cited work
Reference 46
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e3015ca-2b19-46e7-a313-ef08044b9716 · outbound
This paper cites Dewey, Yihao Liu, Yufan He, Scott D.
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI Dewey, Yihao Liu, Yufan He, Scott D
Reference 47
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Pith citing papers
No inbound Pith citation observations are available.