Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:17:01.637758Z
Paper Citation Record · LEDGER
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image
As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.05820.
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 2026-08-08T06:32:00.761636+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
44 of 44 outbound references displayed
- verified exact1
- verified fuzzy35
- unresolved7
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9c6daf74-ab9a-42cf-816d-1db9cfd4bac2 · outbound
This paper cites Topological Similarity Index and Loss Function for Blood Vessel Segmentation.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Topological Similarity Index and Loss Function for Blood Vessel Segmentation
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T10:17:01.805709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 927dd9e4-67cb-4104-a307-edd48792ec42 · outbound
This paper cites V ox2cortex: fast explicit recon- struction of cortical surfaces from 3d mri scans with geomet- ric deep neural networks.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image V ox2cortex: fast explicit recon- struction of cortical surfaces from 3d mri scans with geomet- ric deep neural networks
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.202130Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8cfa0529-679b-46c5-902d-57db46565d2a · outbound
This paper cites 3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image 3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.192273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ba05a120-20cb-4544-aebf-5271a9a688e6 · outbound
This paper cites Deformable convolutional networks.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Deformable convolutional networks
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.183109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2831f548-9f2b-49df-a22a-e5d466a020f7 · outbound
This paper cites Vilac ¸a, Xiyue Wang, Sen Yang, Arcot Sowmya, and Susann Beier.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Vilac ¸a, Xiyue Wang, Sen Yang, Arcot Sowmya, and Susann Beier
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.174563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 180b7e04-bdc6-4740-9382-679cdae07b66 · outbound
This paper cites Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.Scientific Data, 10(1):128,.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.Scientific Data, 10(1):128,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.165119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 22ac3143-81fd-4631-8e0b-e3fffc043c60 · outbound
This paper cites On the history of the min- imum spanning tree problem.Annals of the History of Com- puting, 7(1):43–57, 1985.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image On the history of the min- imum spanning tree problem.Annals of the History of Com- puting, 7(1):43–57, 1985
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.155259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7dc09ed1-4646-4299-83de-4c08e380ccd6 · outbound
This paper cites A fast and efficient technique for the automatic tracing of corneal nerves in confocal microscopy.Translational vision science & technology, 5(5), 2016.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image A fast and efficient technique for the automatic tracing of corneal nerves in confocal microscopy.Translational vision science & technology, 5(5), 2016
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.144836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation aa546028-401c-4456-8947-4408db5ea040 · outbound
This paper cites Topology-preserving deep image segmentation.Advances in neural information processing systems, 32, 2019.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Topology-preserving deep image segmentation.Advances in neural information processing systems, 32, 2019
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.134651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 29c7c7ec-68ba-467f-ba4d-a5c9b49cc11d · outbound
This paper cites The vascular modeling toolkit: a python library for the analysis of tubular structures in medical images.Journal of Open Source Software, 3(25):745, 2018.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image The vascular modeling toolkit: a python library for the analysis of tubular structures in medical images.Journal of Open Source Software, 3(25):745, 2018
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.125132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0f142fe3-8983-4f5b-bf21-c924b69b5262 · outbound
This paper cites IEEE, 2002.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image IEEE, 2002
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.115610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d6708290-50d6-4f94-a898-e447d226adfb · outbound
This paper cites Semi-Supervised Classification with Graph Convolutional Networks.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Semi-Supervised Classification with Graph Convolutional Networks
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:16:59.304805Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 947c61cf-cec0-42d2-8ad4-d22f78746c39 · outbound
This paper cites Learning tree-structured representation for 3d coronary artery segmen- tation.Computerized Medical Imaging and Graphics, 80: 101688, 2020.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Learning tree-structured representation for 3d coronary artery segmen- tation.Computerized Medical Imaging and Graphics, 80: 101688, 2020
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.105991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 61a86e29-18a1-490f-ba63-283cf22be907 · outbound
This paper cites A deep- learning approach for direct whole-heart mesh reconstruc- tion.Medical image analysis, 74:102222, 2021.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image A deep- learning approach for direct whole-heart mesh reconstruc- tion.Medical image analysis, 74:102222, 2021
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.096059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 5f30c527-36b9-4450-9dfd-65da914c2f57 · outbound
This paper cites Building skeleton models via 3-d medial surface axis thin- ning algorithms.CVGIP: Graphical Models and Image Pro- cessing, 56(6):462–478, 1994.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Building skeleton models via 3-d medial surface axis thin- ning algorithms.CVGIP: Graphical Models and Image Pro- cessing, 56(6):462–478, 1994
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.086301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 295d6087-f383-4c97-bda0-af8ed4c11cd6 · outbound
This paper cites an unresolved cited work.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:17:02.076424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ad0642b1-85ef-48c1-bc6b-410b61754137 · outbound
This paper cites Fully convolutional networks for semantic segmentation.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Fully convolutional networks for semantic segmentation
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.066792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a29f4418-9dc4-4b31-bb03-cf4ff7131691 · outbound
This paper cites Decoupled Weight Decay Regularization.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Decoupled Weight Decay Regularization
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fe4bc54-acb6-496f-979d-1f9d1c1e4f47 · outbound
This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image V-net: Fully convolutional neural networks for volumetric medical image segmentation
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.055770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8d54d43c-8c48-4213-937d-eea537ef7cfb · outbound
This paper cites Zeming Lin.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Zeming Lin
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.046177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 90ac437f-bbd0-459f-8015-d389b9f0aa45 · outbound
This paper cites A framework for geo- metric analysis of vascular structures: application to cere- bral aneurysms.IEEE transactions on medical imaging, 28 (8):1141–1155, 2009.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image A framework for geo- metric analysis of vascular structures: application to cere- bral aneurysms.IEEE transactions on medical imaging, 28 (8):1141–1155, 2009
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.036144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b7e0aafc-5945-482d-8882-704e5ede2d51 · outbound
This paper cites Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset.Medical physics, 50(3):1917–1927, 2023.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset.Medical physics, 50(3):1917–1927, 2023
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.025072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1feceace-c0f5-4337-9be0-e98308693536 · outbound
This paper cites Dynamic snake convolution based on topo- logical geometric constraints for tubular structure segmenta- tion.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Dynamic snake convolution based on topo- logical geometric constraints for tubular structure segmenta- tion
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.014356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 5dd7b8d8-d1ff-4194-9d2c-44fc453c90e6 · outbound
This paper cites Heart disease and stroke statistics—2011 update: a re- port from the american heart association.Circulation, 123 (4):e18–e209, 2011.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Heart disease and stroke statistics—2011 update: a re- port from the american heart association.Circulation, 123 (4):e18–e209, 2011
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:02.004074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6d665e80-514c-4830-953a-4c4b8928159f · outbound
This paper cites U- net: Convolutional networks for biomedical image segmen- tation.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image U- net: Convolutional networks for biomedical image segmen- tation
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.993398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 80fe1cae-75c1-412e-92e0-cefb98801198 · outbound
This paper cites Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms.Medical image analysis, 13(5):701–714, 2009.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms.Medical image analysis, 13(5):701–714, 2009
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.983227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a8941a9b-c094-4091-9219-dd81fdd4d3c8 · outbound
This paper cites Deep vessel segmentation by learning graph- ical connectivity.Medical image analysis, 58:101556, 2019.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Deep vessel segmentation by learning graph- ical connectivity.Medical image analysis, 58:101556, 2019
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.971581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f769ae75-6e7d-4386-8a3a-b8539e994a3a · outbound
This paper cites cldice-a novel topology-preserving loss function for tubular structure seg- mentation.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image cldice-a novel topology-preserving loss function for tubular structure seg- mentation
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.961308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation fb847644-088f-4cc9-b6d3-0b0b63dc69a3 · outbound
This paper cites an unresolved cited work.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:17:01.951986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 475b33e7-e705-4151-9ebb-1582563d69b7 · outbound
This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Attention is all you need.Advances in neural information processing systems, 30, 2017
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.942122Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4d8cbd69-4689-4fd3-875c-37af54791d22 · outbound
This paper cites Pointscatter: Point set representation for tubular structure extraction.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Pointscatter: Point set representation for tubular structure extraction
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.932299Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b9446208-7ae2-4381-b06c-18cd6364d28c · outbound
This paper cites Pixel2mesh: Generating 3d mesh models from single rgb images.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Pixel2mesh: Generating 3d mesh models from single rgb images
Reference 32
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d5b935c-bd57-4963-a0c0-eefc228b62f6 · outbound
This paper cites Deep distance transform for tubular structure segmentation in ct scans.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Deep distance transform for tubular structure segmentation in ct scans
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.916215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0cc87ab8-1707-459e-8410-311bb6b7a59b · outbound
This paper cites V oxel2mesh: 3d mesh model genera- tion from volumetric data.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image V oxel2mesh: 3d mesh model genera- tion from volumetric data
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.897113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2e000b3b-6208-41a3-95b4-bf7e5b8b2ca2 · outbound
This paper cites Deep closing: Enhancing topological connectiv- ity in medical tubular segmentation.IEEE Transactions on Medical Imaging, 2024.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Deep closing: Enhancing topological connectiv- ity in medical tubular segmentation.IEEE Transactions on Medical Imaging, 2024
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.888052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e32a42a5-1d38-4683-a732-b8cc36d28d45 · outbound
This paper cites Implicitatlas: learning deformable shape templates in medical imaging.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Implicitatlas: learning deformable shape templates in medical imaging
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.878104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation bbf9258a-4aba-499a-9ce2-a13a2393ad42 · outbound
This paper cites an unresolved cited work.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Unresolved cited work
Reference 37
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:17:01.868529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e4b3a277-ed28-4449-9b1f-7aa172a9b61b · outbound
This paper cites Pro- gressive deep segmentation of coronary artery via hierarchi- cal topology learning.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Pro- gressive deep segmentation of coronary artery via hierarchi- cal topology learning
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.857370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 78cea19e-0797-4988-aae7-0e23290a4133 · outbound
This paper cites Topology-preserving automatic labeling of coronary arteries via anatomy-aware connection classifier.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Topology-preserving automatic labeling of coronary arteries via anatomy-aware connection classifier
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.847104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1d0c43de-a403-4184-b991-2bab923d3b1f · outbound
This paper cites Graphmorph: Tubular structure extraction by morphing pre- dicted graphs.Advances in Neural Information Processing Systems, 37:68472–68499, 2024.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Graphmorph: Tubular structure extraction by morphing pre- dicted graphs.Advances in Neural Information Processing Systems, 37:68472–68499, 2024
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.837358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6c1e4ad6-2965-49b6-8264-e25d4bfbd2d1 · outbound
This paper cites Graph convolution based cross-network multiscale feature fusion for deep vessel segmentation.IEEE Transactions on Med- ical Imaging, 42(1):183–195, 2022.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Graph convolution based cross-network multiscale feature fusion for deep vessel segmentation.IEEE Transactions on Med- ical Imaging, 42(1):183–195, 2022
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.827171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1d5edba8-a396-457c-887f-d21a7b2ec454 · outbound
This paper cites 3d graph anatomy geometry-integrated network for pancre- atic mass segmentation, diagnosis, and quantitative patient management.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image 3d graph anatomy geometry-integrated network for pancre- atic mass segmentation, diagnosis, and quantitative patient management
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:17:01.816815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation fe65251d-0a3c-4ddf-874d-a738a095be21 · outbound
This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Deformable DETR: Deformable Transformers for End-to-End Object Detection
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:17:01.637758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f032b52-db7f-4d2d-9a19-9633da010eeb · outbound
This paper cites an unresolved cited work.
DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Unresolved cited work
Reference 2020
- Resolution
- parse uncertain
- raw_fallback, observed 2026-08-07T10:17:01.906802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
No inbound Pith citation observations are available.