Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-27T17:18:58.300303Z
Paper Citation Record · LEDGER
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis
As of 20 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2606.09400.
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 2026-08-20T06:33:59.587034+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
36 of 36 outbound references displayed
- verified exact6
- verified fuzzy0
- unresolved30
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3de2dcce-a4a0-4bb9-a03b-b91d223f476d · outbound
This paper cites The medical segmentation decathlon.Nature communications, 13(1):4128, 2022.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis The medical segmentation decathlon.Nature communications, 13(1):4128, 2022
Reference 1
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation defaac61-c991-4029-aace-bf6698fcae8a · outbound
This paper cites Merlin: a computed tomography vision–language foundation model and dataset.Nature, pages 1–11, 2026.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Merlin: a computed tomography vision–language foundation model and dataset.Nature, pages 1–11, 2026
Reference 2
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19e9291e-428a-44b9-91b0-9ecb610aaa3c · outbound
This paper cites MONAI: An open-source framework for deep learning in healthcare.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis MONAI: An open-source framework for deep learning in healthcare
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.439057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fe05a95b-80ff-4148-9dca-3a94ed1bd882 · outbound
This paper cites Deep learning-driven pulmonary artery and vein seg- mentation reveals demography-associated vasculature anatomical differences.Nature Communications, 16(1):2262, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Deep learning-driven pulmonary artery and vein seg- mentation reveals demography-associated vasculature anatomical differences.Nature Communications, 16(1):2262, 2025
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e6c44aa-463b-49a5-b865-79e8a3ed85a2 · outbound
This paper cites Maisi: Medical ai for synthetic imaging.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Maisi: Medical ai for synthetic imaging
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d777a6db-25d6-4b13-96c5-2374b269710a · outbound
This paper cites Generalist foundation models from a multimodal dataset for 3d computed tomography.Nature Biomedical Engineering, pages 1–19, 2026.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Generalist foundation models from a multimodal dataset for 3d computed tomography.Nature Biomedical Engineering, pages 1–19, 2026
Reference 6
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19f54254-b330-467a-bde9-5aa9816a42d8 · outbound
This paper cites Mri-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.European Radiology Experimental, 9(1):75, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Mri-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.European Radiology Experimental, 9(1):75, 2025
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bc16e4f1-25d8-4b3b-9d01-fea741aba9ad · outbound
This paper cites Automatic segmentation of cardiovascular structures on chest ct data sets: an update of the totalsegmentator.European journal of radiology, 185:112006, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Automatic segmentation of cardiovascular structures on chest ct data sets: an update of the totalsegmentator.European journal of radiology, 185:112006, 2025
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e791a10-a648-4198-b297-65c8f750f833 · outbound
This paper cites nnu-net revisited: A call for rigorous validation in 3d medical image segmentation.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis nnu-net revisited: A call for rigorous validation in 3d medical image segmentation
Reference 9
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ba7b8f5-d420-4807-a91f-fe6ed5cf7244 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Adam: A Method for Stochastic Optimization
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.447980Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2d0ae5c5-44f5-424d-a21e-36d7382b088d · outbound
This paper cites Skeleton recall loss for connec- tivity conserving and resource efficient segmentation of thin tubular structures.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Skeleton recall loss for connec- tivity conserving and resource efficient segmentation of thin tubular structures
Reference 11
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bda7117c-c9f7-48a1-b6f3-86e13491557a · outbound
This paper cites Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography.European Radiology, 32(9):6037–6045, 2022.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography.European Radiology, 32(9):6037–6045, 2022
Reference 12
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 916c5749-9d1d-4043-adbf-254ade19f21c · outbound
This paper cites an unresolved cited work.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Unresolved cited work
Reference 13
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d31a188f-263c-4869-83e5-2e20ac36b76f · outbound
This paper cites an unresolved cited work.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Unresolved cited work
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70a43e19-e42a-4b02-b4eb-d605c5b53c32 · outbound
This paper cites Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia.European journal of radiology, 150:110259, 2022.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia.European journal of radiology, 150:110259, 2022
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07c23e77-6014-4b63-a621-965571fff196 · outbound
This paper cites Sparse Representation Learning for Vessels.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Sparse Representation Learning for Vessels
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.444765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c773a95f-5102-4cb7-8766-579012e413bd · outbound
This paper cites V oxtell: Free-text promptable universal 3d medical image segmentation, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis V oxtell: Free-text promptable universal 3d medical image segmentation, 2025
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a3b35bb-2366-48f7-b85b-6389919d128c · outbound
This paper cites Vlahavas.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Vlahavas
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d330023f-8bfc-49d2-acd6-0d8f5fa95de2 · outbound
This paper cites Rapid model- guided design of organ-scale synthetic vasculature for biomanufacturing.Science, 388(6752):1198–1204, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Rapid model- guided design of organ-scale synthetic vasculature for biomanufacturing.Science, 388(6752):1198–1204, 2025
Reference 19
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c429155f-ad58-4f5a-b622-a34e8302cb74 · outbound
This paper cites Sexton, Dominic Rütsche, Jessica E.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Sexton, Dominic Rütsche, Jessica E
Reference 20
- Resolution
- verified exact
- doi, observed 2026-06-27T17:21:06.492217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2dfa8e77-0fa4-4153-962a-96c5c8a5f677 · outbound
This paper cites Centerline boundary dice loss for vascular segmentation.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Centerline boundary dice loss for vascular segmentation
Reference 21
- Resolution
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c94eb45-a866-4226-8a0e-8540ba89ade9 · outbound
This paper cites cldice-a novel topology-preserving loss function for tubular structure segmentation.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis cldice-a novel topology-preserving loss function for tubular structure segmentation
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 911f50e1-c2a5-48d0-9db9-7aa1039ed15e · outbound
This paper cites Automated segmentation and quantification of the healthy and diseased aorta in ct angiographies using a dedicated deep learning approach.European Radiology, 32(1):690–701, 2022.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Automated segmentation and quantification of the healthy and diseased aorta in ct angiographies using a dedicated deep learning approach.European Radiology, 32(1):690–701, 2022
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18627669-32c4-4a1e-bde5-0426f199cdaf · outbound
This paper cites A large annotated medical image dataset for the development and evaluation of segmentation algorithms.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:17:29.436288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 754147a2-7750-4e38-b085-f3d71eaef032 · outbound
This paper cites Segmentation of 71 anatomical structures necessary for the evaluation of guideline-conforming clinical target volumes in head and neck cancers.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Segmentation of 71 anatomical structures necessary for the evaluation of guideline-conforming clinical target volumes in head and neck cancers
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07a2f4fc-c206-419b-a17d-036dbd496ce4 · outbound
This paper cites Totalsegmentator: robust segmentation of 104 anatomic structures in ct images.Radiology: Artificial Intelligence, 5(5):e230024, 2023.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Totalsegmentator: robust segmentation of 104 anatomic structures in ct images.Radiology: Artificial Intelligence, 5(5):e230024, 2023
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a3c456d-1b0e-408b-bdf1-0351400583cd · outbound
This paper cites Knowledge-augmented deep learning for segmenting and detecting cerebral aneurysms with ct angiography: a multicenter study.Radiology, 312(2):e233197, 2024.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Knowledge-augmented deep learning for segmenting and detecting cerebral aneurysms with ct angiography: a multicenter study.Radiology, 312(2):e233197, 2024
Reference 27
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16ec5bcd-70e3-44c1-90ff-f31827a7e22b · outbound
This paper cites Simulation-based segmentation of blood vessels in cerebral 3d octa images.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Simulation-based segmentation of blood vessels in cerebral 3d octa images
Reference 28
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2eabdea-fb86-428b-894c-55624d9d5de4 · outbound
This paper cites vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation
Reference 29
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2270a6c1-508b-480e-82bd-72b273eaa664 · outbound
This paper cites Cardiovascular Diseases (CVDs) Fact Sheet.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Cardiovascular Diseases (CVDs) Fact Sheet
Reference 30
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 247e07bf-4ae7-4a9e-842f-5a1c2e8c3145 · outbound
This paper cites Cads: A comprehensive anatomical dataset and segmentation for whole-body anatomy in computed tomography, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Cads: A comprehensive anatomical dataset and segmentation for whole-body anatomy in computed tomography, 2025
Reference 31
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b56be765-64a8-47aa-9dc2-4f997bad7180 · outbound
This paper cites Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA, 2025
Reference 32
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c37f0639-b915-4169-941c-8f07e16fc76c · outbound
This paper cites Yushkevich, Joseph Piven, Heather Cody Hazlett, Rachel Gimpel Smith, Sean Ho, James C.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Yushkevich, Joseph Piven, Heather Cody Hazlett, Rachel Gimpel Smith, Sean Ho, James C
Reference 33
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f767640a-aaaa-44f3-ba43-a94064c785e2 · outbound
This paper cites Adding conditional control to text-to-image diffusion models.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Adding conditional control to text-to-image diffusion models
Reference 34
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee6deca2-0030-4e08-9c40-67b375a6f09b · outbound
This paper cites A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.Nature methods, 22(1):166–176, 2025.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.Nature methods, 22(1):166–176, 2025
Reference 35
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- no resolver link, observed 2026-06-27T17:18:58.300303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd351f9e-698f-4c35-87eb-57a246bbf11a · outbound
This paper cites Complete cardiovascular system in CT.
vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis Complete cardiovascular system in CT
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.441472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.