Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T03:15:40.991541Z
Paper Citation Record · LEDGER
Tractogram foundation model
As of 6 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2606.09893.
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 2026-08-05T06:32:48.257954+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 7bed15c4-52af-4220-ac75-1e904a841a89 · outbound
This paper cites Diffusion mri fiber tractography of the brain.NMR in Biomedicine, 32(4):e3785, 2019.
Tractogram foundation model Diffusion mri fiber tractography of the brain.NMR in Biomedicine, 32(4):e3785, 2019
Reference 1
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Observation 269d7632-586d-49b6-b5d7-d6c6cb58ff37 · outbound
This paper cites Quantitative mapping of the brain’s structural connectivity using diffusion mri tractography: A review.Neuroimage, 249:118870, 2022.
Tractogram foundation model Quantitative mapping of the brain’s structural connectivity using diffusion mri tractography: A review.Neuroimage, 249:118870, 2022
Reference 2
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Observation 13e104bd-309e-4174-8979-f3e25aadeaa1 · outbound
This paper cites Mapping the structural core of human cerebral cortex.PLoS biology, 6(7):e159, 2008.
Tractogram foundation model Mapping the structural core of human cerebral cortex.PLoS biology, 6(7):e159, 2008
Reference 3
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Observation a18c0a00-0228-4d23-83b9-f89b4fd9b57f · outbound
This paper cites Anatomically-constrained tractography: improved diffusion mri streamlines tractography through effective use of anatomical information.Neuroimage, 62(3):1924–1938, 2012.
Tractogram foundation model Anatomically-constrained tractography: improved diffusion mri streamlines tractography through effective use of anatomical information.Neuroimage, 62(3):1924–1938, 2012
Reference 4
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Observation bdcf3fff-b6f4-463b-b093-4d6c08a57ae4 · outbound
This paper cites Anatomical accuracy of brain connections derived from diffu- sion mri tractography is inherently limited.Proceedings of the National Academy of Sciences, 111(46):16574–16579, 2014.
Tractogram foundation model Anatomical accuracy of brain connections derived from diffu- sion mri tractography is inherently limited.Proceedings of the National Academy of Sciences, 111(46):16574–16579, 2014
Reference 5
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Observation 2734602f-2909-4fec-b438-b209d75be93c · outbound
This paper cites Potential and limitations of diffusion mri tractogra- phy for the study of language.Brain and language, 131:65–73, 2014.
Tractogram foundation model Potential and limitations of diffusion mri tractogra- phy for the study of language.Brain and language, 131:65–73, 2014
Reference 6
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Observation 029e6ad6-7fa3-41c5-a2d5-ead2024ecf9c · outbound
This paper cites A diffusion mri tractography connectome of the mouse brain and comparison with neuronal tracer data.
Tractogram foundation model A diffusion mri tractography connectome of the mouse brain and comparison with neuronal tracer data
Reference 7
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Observation 2038ecb4-e8cd-4931-850d-a6bf1f21986c · outbound
This paper cites Brain connectomics predict response to treatment in social anxiety disorder.Molecular psychiatry, 21(5):680–685, 2016.
Tractogram foundation model Brain connectomics predict response to treatment in social anxiety disorder.Molecular psychiatry, 21(5):680–685, 2016
Reference 8
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Observation 6db6042c-db50-45c6-9e88-ce6175b55fc2 · outbound
This paper cites The challenge of mapping the human connectome based on diffusion tractography.Nature communications, 8(1):1349, 2017.
Tractogram foundation model The challenge of mapping the human connectome based on diffusion tractography.Nature communications, 8(1):1349, 2017
Reference 9
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Observation 924a0025-b132-4161-afb9-f5a71a94c03d · outbound
This paper cites Mapping connectomes with diffusion mri: deterministic or probabilistic tractography?Magnetic resonance in medicine, 81(2):1368–1384, 2019.
Tractogram foundation model Mapping connectomes with diffusion mri: deterministic or probabilistic tractography?Magnetic resonance in medicine, 81(2):1368–1384, 2019
Reference 10
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Observation 7a1267a7-fd04-4e60-8c32-fb57e5a54ae0 · outbound
This paper cites Limits to anatomicalaccuracyofdiffusiontractographyusing modernapproaches.Neuroimage, 185:1–11, 2019.
Tractogram foundation model Limits to anatomicalaccuracyofdiffusiontractographyusing modernapproaches.Neuroimage, 185:1–11, 2019
Reference 11
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Observation 58006977-4594-4149-967b-5ac1cf73adb4 · outbound
This paper cites Mapping structural connectivity using diffusion mri: Challenges and opportunities.Journal of Magnetic Resonance Imaging, 53(6):1666–1682, 2021.
Tractogram foundation model Mapping structural connectivity using diffusion mri: Challenges and opportunities.Journal of Magnetic Resonance Imaging, 53(6):1666–1682, 2021
Reference 12
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Observation e79f3f3e-8b66-4d5a-88cd-c5ef4e84e5dc · outbound
This paper cites Think deep in the tractography game: deep learning for tractography comput- ing and analysis.Brain Structure and Function, 230(6):100, 2025.
Tractogram foundation model Think deep in the tractography game: deep learning for tractography comput- ing and analysis.Brain Structure and Function, 230(6):100, 2025
Reference 13
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Observation 1973d995-d02b-400b-a05f-b6e68023cc0c · outbound
This paper cites Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023.
Tractogram foundation model Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023
Reference 14
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Observation 96652340-ac19-4035-ac4e-fe2cfdfa6d5e · outbound
This paper cites Foundation models in radiology: what, how, why, and why not.Radiology, 314(2):e240597, 2025.
Tractogram foundation model Foundation models in radiology: what, how, why, and why not.Radiology, 314(2):e240597, 2025
Reference 15
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Observation 68669ef9-d114-420e-970d-dc94ffbe7c63 · outbound
This paper cites Foun- dation model for cancer imaging biomarkers.Nature machine intelligence, 6(3):354–367, 2024.
Tractogram foundation model Foun- dation model for cancer imaging biomarkers.Nature machine intelligence, 6(3):354–367, 2024
Reference 16
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Observation 682aeb69-b39a-4b48-bc51-78a93a533601 · outbound
This paper cites Towards generalist foundation model for radiology by leveraging web-scale 2d&3d medical data.Nature Communications, 16(1):7866, 2025.
Tractogram foundation model Towards generalist foundation model for radiology by leveraging web-scale 2d&3d medical data.Nature Communications, 16(1):7866, 2025
Reference 17
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Observation 51d8eb19-5474-4c96-a73e-e635240bb421 · outbound
This paper cites An mri–pathology foundation model for noninvasive diagnosis and grading of prostate cancer.Nature Cancer, 6(10):1621–1637, 2025.
Tractogram foundation model An mri–pathology foundation model for noninvasive diagnosis and grading of prostate cancer.Nature Cancer, 6(10):1621–1637, 2025
Reference 18
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Observation fb6b2ef5-7daf-4466-be68-593b1a225fa0 · outbound
This paper cites A foundation model for lesion 17 segmentation on brain mri with mixture of modality experts.IEEE Transactions on Medical Imaging, 2025.
Tractogram foundation model A foundation model for lesion 17 segmentation on brain mri with mixture of modality experts.IEEE Transactions on Medical Imaging, 2025
Reference 19
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Observation f6c2985b-208d-440e-89b6-1114965a69a8 · outbound
This paper cites Millennium pathways for tractography: 40 grand challenges to shape the future of tractography.ArXiv, pages arXiv–2509, 2025.
Tractogram foundation model Millennium pathways for tractography: 40 grand challenges to shape the future of tractography.ArXiv, pages arXiv–2509, 2025
Reference 20
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Observation dbb85aa1-4759-4cc7-bc15-95437832f6d9 · outbound
This paper cites An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan.Neuroimage, 179:429–447, 2018.
Tractogram foundation model An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan.Neuroimage, 179:429–447, 2018
Reference 21
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Observation 90e8d945-2536-4cba-9b12-9fae2398ca4b · outbound
This paper cites Deep white matter analysis (deepwma): Fast and consistent tractography segmentation.Med.
Tractogram foundation model Deep white matter analysis (deepwma): Fast and consistent tractography segmentation.Med
Reference 22
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Observation dabc95ed-ad54-401b-a5ff-126eca9ac771 · outbound
This paper cites Tractcloud: Registration-free tractography parcellation with a novel local-global streamline point cloud representation.
Tractogram foundation model Tractcloud: Registration-free tractography parcellation with a novel local-global streamline point cloud representation
Reference 23
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Observation 3c7dc378-fdef-4aec-91c8-77a7cffcd3f6 · outbound
This paper cites an unresolved cited work.
Tractogram foundation model Unresolved cited work
Reference 24
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Observation 49183049-0765-45ab-a72b-10b78397164c · outbound
This paper cites Dynamic graph cnn for learning on point clouds.ACM Trans.
Tractogram foundation model Dynamic graph cnn for learning on point clouds.ACM Trans
Reference 25
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Observation f4d5ce7d-cd10-486d-81c5-dd4021563d60 · outbound
This paper cites Rapidparc: A global-context transformer for parallel, accurate, and lesion- robust tractogram parcellation.Imaging Neuroscience, 4:IMAG–a, 2026.
Tractogram foundation model Rapidparc: A global-context transformer for parallel, accurate, and lesion- robust tractogram parcellation.Imaging Neuroscience, 4:IMAG–a, 2026
Reference 26
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Observation 1040f9ca-fe7a-4943-bb37-c3e3033d0526 · outbound
This paper cites Prediction of individual subject’s age across the human lifespan using diffusion tensor imaging: a machine learning approach.
Tractogram foundation model Prediction of individual subject’s age across the human lifespan using diffusion tensor imaging: a machine learning approach
Reference 27
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Observation 2c1e0cfe-aab4-4ef7-8639-273b713f9fe6 · outbound
This paper cites Modelandpredictageandsex inhealthysubjectsusing brain white matterfeatures: a deep learning approach.
Tractogram foundation model Modelandpredictageandsex inhealthysubjectsusing brain white matterfeatures: a deep learning approach
Reference 28
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Observation 73979104-b301-42be-8234-75533c2f64fa · outbound
This paper cites Tractgraphcnn: anatomically informed graph cnn for classification using diffusion mri tractography.
Tractogram foundation model Tractgraphcnn: anatomically informed graph cnn for classification using diffusion mri tractography
Reference 29
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Observation 0c7b7dd5-09fd-467e-aec1-34caee4176b3 · outbound
This paper cites Tractgraphformer: Anatomically informed hybrid graph cnn-transformer network for interpretable sex and age prediction from diffusion mri tractography.Med.
Tractogram foundation model Tractgraphformer: Anatomically informed hybrid graph cnn-transformer network for interpretable sex and age prediction from diffusion mri tractography.Med
Reference 30
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Observation c65df897-6fca-4ca1-afe2-2f916a59146c · outbound
This paper cites Global fiber reconstruction becomes practical.Neuroimage, 54(2):955– 962, 2011.
Tractogram foundation model Global fiber reconstruction becomes practical.Neuroimage, 54(2):955– 962, 2011
Reference 31
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Observation c03dbbed-9500-4924-9bf4-4ab3939e0e09 · outbound
This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.
Tractogram foundation model Pointnet: Deep learning on point sets for 3d classification and segmentation
Reference 32
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Observation bb7f2a53-9d21-49c9-acdb-1eeaafb52117 · outbound
This paper cites Predicting age across hu- man lifespan based on structural connectivity from diffusion tensor imaging.
Tractogram foundation model Predicting age across hu- man lifespan based on structural connectivity from diffusion tensor imaging
Reference 33
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Observation 783e1db0-eed4-4ccc-afec-b4178d6cfd01 · outbound
This paper cites Predictability of intelligence and age from structural connec- tomes.Plos one, 19(4):e0301599, 2024.
Tractogram foundation model Predictability of intelligence and age from structural connec- tomes.Plos one, 19(4):e0301599, 2024
Reference 34
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Observation 02878ef2-1683-4fe5-8eab-579a19127112 · outbound
This paper cites brain-age.
Tractogram foundation model brain-age
Reference 35
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Observation 319a9059-442b-43f3-9dcd-bcca1605cadf · outbound
This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020.
Tractogram foundation model Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020
Reference 36
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Observation 21b967e5-b4fa-4770-ba1d-b7ad837c1706 · outbound
This paper cites Self-supervised learning in medicine and healthcare.Nature Biomedical Engineering, 6(12):1346–1352, 2022.
Tractogram foundation model Self-supervised learning in medicine and healthcare.Nature Biomedical Engineering, 6(12):1346–1352, 2022
Reference 37
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Observation 1244d000-eb55-4507-ae80-cbf27368e13a · outbound
This paper cites Masked autoencoders are scalable vision learners.
Tractogram foundation model Masked autoencoders are scalable vision learners
Reference 38
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Observation ba2b695e-1fad-4593-86a7-accc32a738c4 · outbound
This paper cites Predicting clinical outcome of stroke patients with tractographic feature.
Tractogram foundation model Predicting clinical outcome of stroke patients with tractographic feature
Reference 39
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Observation 3c3b1f15-0431-401c-a511-94fb656243a8 · outbound
This paper cites Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.Brain, 145(2):457–475, 2022.
Tractogram foundation model Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.Brain, 145(2):457–475, 2022
Reference 40
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Observation a1e342b8-04a9-422d-949e-546524d89234 · outbound
This paper cites Tractography- based modeling explains treatment outcomes in patients undergoing deep brain stimulation for obsessive-compulsive disorder.Biological psychiatry, 96(2):95–100, 2024.
Tractogram foundation model Tractography- based modeling explains treatment outcomes in patients undergoing deep brain stimulation for obsessive-compulsive disorder.Biological psychiatry, 96(2):95–100, 2024
Reference 41
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Observation 75b75c44-f16f-4f45-89f4-8af2838ec0cc · outbound
This paper cites The wu-minn human connectome project: an overview.Neuroimage, 80:62–79, 2013.
Tractogram foundation model The wu-minn human connectome project: an overview.Neuroimage, 80:62–79, 2013
Reference 42
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Observation e197e08c-c0f5-4ad3-895d-dc858f208f02 · outbound
This paper cites The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.Molecular psychiatry, 19(6):659–667, 2014.
Tractogram foundation model The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.Molecular psychiatry, 19(6):659–667, 2014
Reference 43
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Observation a822f9a4-9d52-44aa-a864-8dd765f10534 · outbound
This paper cites The alzheimer’s disease neuroimaging initiative.Neuroimaging Clinics, 15(4):869–877, 2005.
Tractogram foundation model The alzheimer’s disease neuroimaging initiative.Neuroimaging Clinics, 15(4):869–877, 2005
Reference 44
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Observation 7425d300-d789-4b49-9c27-529b3a79cf9c · outbound
This paper cites A phenome-wide examination of neural and cognitive function.Scientific data, 3(1):160110, 2016.
Tractogram foundation model A phenome-wide examination of neural and cognitive function.Scientific data, 3(1):160110, 2016
Reference 45
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Observation f9f04144-f797-432d-8b18-31ebb86714ef · outbound
This paper cites The parkinson progression marker initiative (ppmi).Progress in neurobiology, 95(4):629–635, 2011.
Tractogram foundation model The parkinson progression marker initiative (ppmi).Progress in neurobiology, 95(4):629–635, 2011
Reference 46
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Observation 73e65c86-bab7-4bc0-bf8e-d311251127a8 · outbound
This paper cites Scikit- learn: Machine learning in python.Journal of machine learning research, 12:2825–2830, 2011.
Tractogram foundation model Scikit- learn: Machine learning in python.Journal of machine learning research, 12:2825–2830, 2011
Reference 47
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Pith citing papers
No inbound Pith citation observations are available.