Paper Citation Record · LEDGER

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation

As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.23086.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.23086 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:54:43.792514Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

verified exact0
verified fuzzy20
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0fca66c5-a78f-4df6-8b42-3b84b1afae7a · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.284316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 274fc000-99b8-40d9-a8bd-c23f82324aa1 · outbound

This paper cites IEEE Transactions on Medical Imaging, 40(1), 262-273 (2020).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation IEEE Transactions on Medical Imaging, 40(1), 262-273 (2020)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.262316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fecd1543-79e9-4d93-afb4-05d56e1d5700 · outbound

This paper cites A., Išgum, I.: Iterative fully con- volutional neural networks for automatic vertebra segmentation and identification.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation A., Išgum, I.: Iterative fully con- volutional neural networks for automatic vertebra segmentation and identification

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.232283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98cfb092-0ab5-463b-bfc0-02cf22d551ab · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Medical Image Computing and Computer Assisted Intervention, pp

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.216382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6f799494-1358-4104-9ab4-5ebbea175158 · outbound

This paper cites Medical Image Analysis, 75, 102258 (2022).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation Medical Image Analysis, 75, 102258 (2022)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.182756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation afefc666-448c-4c46-ad53-941468e60048 · outbound

This paper cites IEEE Journal of Biomedical and Health Informatics, 26(8), 3976-3987 (2022).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation IEEE Journal of Biomedical and Health Informatics, 26(8), 3976-3987 (2022)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.163763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 310e9a90-85a3-4dc7-b684-e5401f85ee22 · outbound

This paper cites In: Medical Image Computing and Com- puter Assisted Intervention, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Medical Image Computing and Com- puter Assisted Intervention, pp

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.147354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 720809c6-0f35-4a46-9778-f8c63e536069 · outbound

This paper cites In: International Symposium on Biomedical Imaging, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: International Symposium on Biomedical Imaging, pp

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.132046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 957b0c90-17e5-4100-8d34-c00885223c6d · outbound

This paper cites Medical Physics, 50(10), 6296-6318 (2023).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation Medical Physics, 50(10), 6296-6318 (2023)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.116129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d583f65a-7853-44b5-a73d-4ad9afc00d85 · outbound

This paper cites T., Warrington, A., Linderman, S.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation T., Warrington, A., Linderman, S

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.100468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0f9547b1-d18f-424e-a147-c83055a5b087 · outbound

This paper cites In: First Conference on Language Modeling.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: First Conference on Language Modeling

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.082702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 261a5da0-cc28-490e-be7c-1c3a90f4345b · outbound

This paper cites Pattern Recognition, 143, 109819 (2023).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation Pattern Recognition, 143, 109819 (2023)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.065857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 60750af6-3283-441f-8cdf-b1cb243ed8a6 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.049283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fef30359-a59f-4057-b9a2-505b1a948d1c · outbound

This paper cites Neural Networks, 107: 3-11 (2018).

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation Neural Networks, 107: 3-11 (2018)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.030748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d806d860-f075-46e2-84fc-b63cc1541019 · outbound

This paper cites E., Bayat, A., Löffler, M., Liebl, H., Li, H., Kirschke, J.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation E., Bayat, A., Löffler, M., Liebl, H., Li, H., Kirschke, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:44.013522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 13aa10f3-2c9d-468c-9988-5f8cc664e372 · outbound

This paper cites A., Becherucci, E.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation A., Becherucci, E

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:43.991447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d09c8453-3756-4d94-a4bd-ba19d9954f68 · outbound

This paper cites F., Kohl, S.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation F., Kohl, S

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:43.972325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e2cfd7b-5241-46ab-8ce7-6afcdf80171f · outbound

This paper cites R., Landman, B., Xu, D., Hatamizadeh, A.: Self-supervised pre-training of swin transformers for 3d medical image analysis.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation R., Landman, B., Xu, D., Hatamizadeh, A.: Self-supervised pre-training of swin transformers for 3d medical image analysis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:43.951268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2038dc0-6ec1-4da9-b8a0-a6f655d9b52e · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Medical Image Computing and Computer Assisted Intervention, pp

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:43.930458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9d24edd9-7260-4481-bbb4-cdca37d4f50f · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T21:54:43.776340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac5ef6e9-1245-460a-84dd-bb3f6ae2a6ea · outbound

This paper cites In: Medical Image Computing and Computer-Assisted Intervention, pp.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation In: Medical Image Computing and Computer-Assisted Intervention, pp

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:54:43.911585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3bbc6796-9192-41d3-893c-5275a4ee0f7e · outbound

This paper cites MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image Segmentation.

Frequency-enhanced Multi-granularity Context Network for Efficient Vertebrae Segmentation MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image Segmentation

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T21:54:43.849597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.