Paper Citation Record · LEDGER

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones

As of 22 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.22803.

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

pith.paper-citation-record.v1
2607.22803 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T04:56:42.580530Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

33 of 33 outbound references displayed

verified exact6
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 681211da-642d-4803-8b31-8e6867ce41b1 · outbound

This paper cites IEEE Transactions on Biomedical Engineering43(6), 638–649 (1996).https://doi.org/10.1109/10.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones IEEE Transactions on Biomedical Engineering43(6), 638–649 (1996).https://doi.org/10.1109/10

Reference 1

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Observation f11e9f4d-0b23-4e39-a521-96b93b42c586 · outbound

This paper cites X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery

Reference 2

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Observation 5d4a1452-8db9-4181-bde9-62a5ce4c58c6 · outbound

This paper cites International Journal of Sustainable Construction and Design 7(1) (2016).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones International Journal of Sustainable Construction and Design 7(1) (2016)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.447750Z

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Observation 4dcd08b3-1b22-44ef-bae3-d238a2e9dcf1 · outbound

This paper cites Machine Vision and Applica- tions37(1), 2 (2025).https://doi.org/10.1007/s00138-025-01763-z 16 R.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Machine Vision and Applica- tions37(1), 2 (2025).https://doi.org/10.1007/s00138-025-01763-z 16 R

Reference 4

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Observation 05ef126b-722c-4d71-ac16-250f84ca0c44 · outbound

This paper cites Physics in Medicine & Biology61(8), 3009–3025 (2016).https://doi.org/10.1088/0031-9155/61/8/3009.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Physics in Medicine & Biology61(8), 3009–3025 (2016).https://doi.org/10.1088/0031-9155/61/8/3009

Reference 5

Resolution: verified exact; doi, observed 2026-08-01T04:59:19.025762Z

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Observation e2cce847-b681-4fbc-8e7a-5cd80385e804 · outbound

This paper cites Journal of Biomechanical Engineering127(4), 692–699 (2005).https: //doi.org/10.1115/1.1933949.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Journal of Biomechanical Engineering127(4), 692–699 (2005).https: //doi.org/10.1115/1.1933949

Reference 6

Resolution: verified exact; doi, observed 2026-08-01T04:59:18.935759Z

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Observation 4b3b2d11-528e-4824-96d7-26f7d11fe69c · outbound

This paper cites Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration

Reference 7

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Observation 40a31cec-6a0b-4552-81d1-a4afc6b6f041 · outbound

This paper cites Rapid patient-specific neural networks for intraoperative X-ray to volume registration.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Rapid patient-specific neural networks for intraoperative X-ray to volume registration

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.470631Z

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Observation e5153c2c-d4fb-4178-9d04-46aedd8ff88c · outbound

This paper cites Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.474968Z

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Observation ef9fb854-b734-46a2-9b5d-badc8524d651 · outbound

This paper cites Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.479487Z

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Observation 814cc545-d27e-4412-bbd3-ec50bb636442 · outbound

This paper cites International Journal of Computer Assisted Radiology and Surgery15(5), 759–769 (2020).https://doi.org/10.1007/s11548-020-02162-7.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones International Journal of Computer Assisted Radiology and Surgery15(5), 759–769 (2020).https://doi.org/10.1007/s11548-020-02162-7

Reference 11

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Observation d23c55a4-377c-4f21-8532-900dfa4f0baf · outbound

This paper cites In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.487842Z

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Observation 5d28e02b-18d8-41eb-9488-39dd33ba267c · outbound

This paper cites In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.492312Z

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Observation f348d1f0-368c-4e0b-901b-bbf90252d61e · outbound

This paper cites In: International Conference on Computer Vision (ICCV).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: International Conference on Computer Vision (ICCV)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.496573Z

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Observation c3a09fbd-b2ee-42be-9d84-7ea3ddaa0eb0 · outbound

This paper cites The Journal of Arthroplasty38(10), 2068–2074 (2023).https://doi.org/10.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones The Journal of Arthroplasty38(10), 2068–2074 (2023).https://doi.org/10

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.500701Z

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Observation 0a1a3d7b-713d-4c99-8335-7ad2c718839f · outbound

This paper cites Journal of Biomechanics36(6), 873–882 (2003).https://doi.org/10.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Journal of Biomechanics36(6), 873–882 (2003).https://doi.org/10

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.504901Z

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Observation 60828422-c825-4edc-b832-6465452443fb · outbound

This paper cites IEEE Transactions on Medical Imaging24(9), 1177–1189 (2005).https://doi.org/10.1109/TMI.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones IEEE Transactions on Medical Imaging24(9), 1177–1189 (2005).https://doi.org/10.1109/TMI

Reference 17

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Observation 7bcb1787-a502-4f5e-a1f2-c44a70209ba5 · outbound

This paper cites In: European Conference on Computer Vision (ECCV).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: European Conference on Computer Vision (ECCV)

Reference 18

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Observation 04c24dd3-84b2-4e9d-a6ef-8df34c15eee5 · outbound

This paper cites In: Conference on Robot Learning (CoRL) (2022).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: Conference on Robot Learning (CoRL) (2022)

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.517169Z

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Observation f85698d9-72af-4f81-83b7-c6fbd2b63a0c · outbound

This paper cites In: European Conference on Computer Vision (ECCV).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: European Conference on Computer Vision (ECCV)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.521374Z

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Observation 2dd9d7a6-b7ee-4910-9e05-00d7b609df32 · outbound

This paper cites IEEE Transactions on Medical Imaging22(12), 1561–1574 (2003).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones IEEE Transactions on Medical Imaging22(12), 1561–1574 (2003)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.526551Z

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Observation dd59cda2-877f-41ee-b9d8-b7146de0e9d7 · outbound

This paper cites Medical Image Analysis16(3), 642–661 (2012).https://doi.org/10.1016/j.media.2010.03.005.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Medical Image Analysis16(3), 642–661 (2012).https://doi.org/10.1016/j.media.2010.03.005

Reference 22

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Observation 3e700c12-9d82-4a05-a680-078e08bb8e7c · outbound

This paper cites IEEE Transactions on Medical Imaging31(4), 948–962 (2012).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones IEEE Transactions on Medical Imaging31(4), 948–962 (2012)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.535079Z

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Observation 751d2fd2-8d31-4bbd-9049-665697c2ee07 · outbound

This paper cites IEEE Transactions on Medical Imaging17(4), 586–595 (1998).https://doi.org/ 10.1109/42.730403.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones IEEE Transactions on Medical Imaging17(4), 586–595 (1998).https://doi.org/ 10.1109/42.730403

Reference 24

Resolution: verified exact; doi, observed 2026-08-01T04:59:18.865134Z

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Observation ee55b554-bf92-4227-9a6a-c7841747ae2f · outbound

This paper cites Os- teoarthritis and Cartilage16(12), 1433–1441 (2008).https://doi.org/10.1016/ j.joca.2008.06.016.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Os- teoarthritis and Cartilage16(12), 1433–1441 (2008).https://doi.org/10.1016/ j.joca.2008.06.016

Reference 25

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Observation 19448940-97b7-4205-a3f9-a2930789fa3a · outbound

This paper cites Medical Engineering & Physics77, 107–113 (2020).https: //doi.org/10.1016/j.medengphy.2020.01.002.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Medical Engineering & Physics77, 107–113 (2020).https: //doi.org/10.1016/j.medengphy.2020.01.002

Reference 26

Resolution: verified exact; doi, observed 2026-08-01T04:59:18.733557Z

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Observation 85b0d9ff-46da-4771-8d82-4e3adfca3c0e · outbound

This paper cites Proceedings of the Institution of Mechanical Engineers, Part H225(8), 753–761 (2011).https://doi.org/10.1177/0954411911407669.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Proceedings of the Institution of Mechanical Engineers, Part H225(8), 753–761 (2011).https://doi.org/10.1177/0954411911407669

Reference 27

Resolution: verified exact; doi, observed 2026-08-01T04:59:18.575908Z

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Observation 496a17af-6f36-47e8-9efa-26a2df6db408 · outbound

This paper cites X-Ray to CT Rigid Registration Using Scene Coordinate Regression.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones X-Ray to CT Rigid Registration Using Scene Coordinate Regression

Reference 28

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Observation 9b4206c8-4062-4de5-8f85-064678db5f63 · outbound

This paper cites RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.562244Z

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Observation 67ef99fc-9a79-4d88-935b-2fb3f7241af7 · outbound

This paper cites Daems et al.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Daems et al

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.566829Z

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Observation 2e0e7c88-55cd-4fdd-929f-636d86aa7496 · outbound

This paper cites PLOS ONE17(6), e0270596 (2022).https://doi.org/10.1371/ journal.pone.0270596.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones PLOS ONE17(6), e0270596 (2022).https://doi.org/10.1371/ journal.pone.0270596

Reference 31

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Observation b3191141-5777-44d0-9458-42e7d4cbae09 · outbound

This paper cites In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019).

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.576510Z

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Observation 5d0dc395-9c85-4a92-81fa-8a494d98f72e · outbound

This paper cites Radiology: Ar- tificial Intelligence5(5), e230024 (2023).https://doi.org/10.1148/ryai.230024.

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones Radiology: Ar- tificial Intelligence5(5), e230024 (2023).https://doi.org/10.1148/ryai.230024

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T04:56:42.580530Z

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Pith citing papers

No inbound Pith citation observations are available.