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Paper Citation Record · LEDGER

Rapid patient-specific neural networks for intraoperative X-ray to volume registration

As of 22 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 2 inbound Pith citation observations for arXiv:2503.16309.

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

pith.paper-citation-record.v1
2503.16309 v2

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-22T23:14:26.488603Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T04:56:42.470631Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

83 of 83 outbound references displayed

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  • verified fuzzy76
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 739987de-d9d0-4079-9fd8-34c831383b8f · outbound

This paper cites Patient exposure from radiologic and nuclear medicine procedures in the united states and worldwide: 2009–2018.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Patient exposure from radiologic and nuclear medicine procedures in the united states and worldwide: 2009–2018

Reference 1

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Observation b73373e3-47ad-45e1-9aad-44ca2581fb10 · outbound

This paper cites Intraoperative image guidance in neurosurgery: devel- opment, current indications, and future trends.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Intraoperative image guidance in neurosurgery: devel- opment, current indications, and future trends

Reference 2

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Source-reported events for the cited work

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Observation b368726c-d97b-4705-ba75-2ceedda17ad1 · outbound

This paper cites The role of imaging in the develop- ment of neurosurgery.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration The role of imaging in the develop- ment of neurosurgery

Reference 3

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Observation 6ba02c47-fb47-4d86-a506-a5510009f6d9 · outbound

This paper cites Image guided orthopaedic surgery design and analy- sis.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Image guided orthopaedic surgery design and analy- sis

Reference 4

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation efadd185-faae-4e59-b372-d25b75d557ba · outbound

This paper cites Image-guided surgery: from x-rays to virtual reality.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Image-guided surgery: from x-rays to virtual reality

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3ffcf347-b0ae-47d3-a7bc-cfbe02b95636 · outbound

This paper cites Endovascular image-guided interventions (eigis).

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Endovascular image-guided interventions (eigis)

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9ff243f6-f698-47fd-adc5-89840c2d5459 · outbound

This paper cites Image guidance for endovascular repair of complex aortic aneurysms: comparison of two- dimensional and three-dimensional angiography and image fusion.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Image guidance for endovascular repair of complex aortic aneurysms: comparison of two- dimensional and three-dimensional angiography and image fusion

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8403ba88-9099-4c25-ae8b-ca6e1952e5bb · outbound

This paper cites X-ray volumetric imaging in image-guided radiotherapy: the new standard in on-treatment imaging.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration X-ray volumetric imaging in image-guided radiotherapy: the new standard in on-treatment imaging

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7f85bc63-e1eb-429a-b306-b77bbfc32213 · outbound

This paper cites Advances in image-guided radiation therapy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Advances in image-guided radiation therapy

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8d4690b0-8f03-4775-96c5-b50537a9cc98 · outbound

This paper cites Image-guided radiotherapy: a new dimension in radiation oncology.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Image-guided radiotherapy: a new dimension in radiation oncology

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e9ba9f2f-fcaa-4e7b-9344-61fa924a4456 · outbound

This paper cites The interventionalism of medicine: in- terventional radiology, cardiology, and neuroradiology.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration The interventionalism of medicine: in- terventional radiology, cardiology, and neuroradiology

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 52f21696-f7e5-4ab5-9d58-49268997fa33 · outbound

This paper cites Diagnostic and interventional radiology.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Diagnostic and interventional radiology

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 36c2ebe7-beec-4c88-864c-8ee565438c50 · outbound

This paper cites Imaging in interventional radi- ology: 2043 and beyond.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Imaging in interventional radi- ology: 2043 and beyond

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation eb741cc9-83a6-421b-9df0-6fd14191bf5c · outbound

This paper cites Importance of dose settings in the x-ray systems used for interventional radiology: a national survey.Car- diovascular and interventional radiology, 32:121–126.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Importance of dose settings in the x-ray systems used for interventional radiology: a national survey.Car- diovascular and interventional radiology, 32:121–126

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d4d931df-581a-4f1a-8ea5-988bb14c1013 · outbound

This paper cites Five-year outcomes of transcatheter or surgical aortic-valve replacement.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Five-year outcomes of transcatheter or surgical aortic-valve replacement

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 759a8ca0-79c5-42a9-be23-028206c096cf · outbound

This paper cites an unresolved cited work.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f57888f6-ebb4-4bda-95e5-6942e063bf74 · outbound

This paper cites Imaging of interventional therapies in oncology: Image guidance, robotics, and fusion systems.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Imaging of interventional therapies in oncology: Image guidance, robotics, and fusion systems

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7f4c4d0f-73a6-43de-a407-b6170da23349 · outbound

This paper cites Wrong-sided and wrong-level neurosurgery: a national survey.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Wrong-sided and wrong-level neurosurgery: a national survey

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 048c101f-d861-4652-9428-e4f48be7da2f · outbound

This paper cites The prevalence of wrong level surgery among spine sur- geons.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration The prevalence of wrong level surgery among spine sur- geons

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3b519741-48dd-4522-b9fd-0397ec45e75b · outbound

This paper cites Handbook of interventional radiologic procedures.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Handbook of interventional radiologic procedures

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 097f9186-993d-498b-aff0-a66d6064f9a3 · outbound

This paper cites Role of 3d intraoperative imaging in orthopedic and trauma surgery.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Role of 3d intraoperative imaging in orthopedic and trauma surgery

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0d816e30-83dd-4c41-8551-82b681770907 · outbound

This paper cites Machine learning for automated and real-time two-dimensional to three- dimensional registration of the spine using a single radiograph.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Machine learning for automated and real-time two-dimensional to three- dimensional registration of the spine using a single radiograph

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 14640666-e163-4df5-b9d3-a8c6a03a9b8a · outbound

This paper cites Method and device for displaying a first image and a second image of an object, March 6 2018.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Method and device for displaying a first image and a second image of an object, March 6 2018

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 79235bd9-11ca-4522-8872-abcbc04b4d1d · outbound

This paper cites A hybrid 3d-2d image registration framework for pedicle screw trajectory registration between intraoper- ative x-ray image and preoperative ct image.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A hybrid 3d-2d image registration framework for pedicle screw trajectory registration between intraoper- ative x-ray image and preoperative ct image

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0cbfd35d-34ae-45ec-9ff3-b986f80c96df · outbound

This paper cites Patient specific 4d coronary models from ecg-gated cta data for intra-operative dynamic alignment of cta with x-ray images.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Patient specific 4d coronary models from ecg-gated cta data for intra-operative dynamic alignment of cta with x-ray images

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f837c9c3-2387-4e37-917f-37bbf112644f · outbound

This paper cites Epipolar consistency in transmission imaging.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Epipolar consistency in transmission imaging

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.463917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation bf7d3464-b02e-4075-905c-e100a691869c · outbound

This paper cites 4d interventional device recon- struction from biplane fluoroscopy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration 4d interventional device recon- struction from biplane fluoroscopy

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2c95e0e3-20de-47a3-81a7-638254f0deb1 · outbound

This paper cites Image registration and data fusion in radiation therapy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Image registration and data fusion in radiation therapy

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.340146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6810d0b3-fe5b-4305-b75d-7d3aa91733cd · outbound

This paper cites Artificial intelligence in radiation oncol- ogy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Artificial intelligence in radiation oncol- ogy

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.351136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 593c0fd7-552f-43d6-90ed-095dcd74f6e9 · outbound

This paper cites A robotic electromagnetic navigation bronchoscopy with integrated tool-in-lesion- tomosynthesis technology: The MATCH study.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A robotic electromagnetic navigation bronchoscopy with integrated tool-in-lesion- tomosynthesis technology: The MATCH study

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.296180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:ddb2f3d97c89d45e335a6e6125e806632aabade7e2cab609b041c727918b8fed

Observation bcd59fbd-2173-4d22-9221-e7493037fbed · outbound

This paper cites Telerobotic neurovascular interventions with mag- netic manipulation.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Telerobotic neurovascular interventions with mag- netic manipulation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.336471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d3a678a5-043f-486d-bc89-76575da5c236 · outbound

This paper cites The impact of machine learning on 2D/3D registration for image-guided interventions: A systematic review and perspective.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration The impact of machine learning on 2D/3D registration for image-guided interventions: A systematic review and perspective

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.456202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:050605be6a90009cfd5d6bb5ca30458881d1b4fb32347f6c2a75ef5334150158

Observation 740b6815-793a-415a-ad0b-c86027e126b0 · outbound

This paper cites Patient setup error measurement using 3d intensity-based im- age registration techniques.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Patient setup error measurement using 3d intensity-based im- age registration techniques

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.422387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:745724fb091e464f1063d9641784a42107fe7641feeb89a2ef32bb225cdd0b13

Observation e5cc18c4-178b-491f-b269-cec4c53f8c56 · outbound

This paper cites A patient-to-computed-tomography image reg- istration method based on digitally reconstructed radio- graphs.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A patient-to-computed-tomography image reg- istration method based on digitally reconstructed radio- graphs

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.393500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:aaceb161a1d8e614ef201f443f9a67a6034c258d2cd543e5dc8bd6e0104e3900

Observation 2979a294-d34a-4ad4-93a9-56331110b55f · outbound

This paper cites A comparison of similarity measures for use in 2-d-3-d medical image registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A comparison of similarity measures for use in 2-d-3-d medical image registration

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.425727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:161012e6254563a714fa60fa03b0e33da4ec20eff0912abffaad361f9597e08d

Observation 43c0641f-b33e-4b16-be37-1ba7eea1ae46 · outbound

This paper cites Effective intensity- based 2d/3d rigid registration between fluoroscopic x- ray and ct.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Effective intensity- based 2d/3d rigid registration between fluoroscopic x- ray and ct

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.450044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:55bdfafabd33a54cdc8ee2dce2a672699eec6655d759482c7ebfc33e99d216cd

Observation f741480f-a4df-4be9-8336-01b17059de0e · outbound

This paper cites 2d-3d rigid registration of x-ray fluoroscopy and ct im- ages using mutual information and sparsely sampled histogram estimators.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration 2d-3d rigid registration of x-ray fluoroscopy and ct im- ages using mutual information and sparsely sampled histogram estimators

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.365979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:e98e256f36c715bdaa9b7af640874c7498e2c3d7ba32da936a5e9d04871ec216

Observation 60f09035-60e0-458d-a2f0-8fc4ccff5235 · outbound

This paper cites Fast auto- differentiable digitally reconstructed radiographs for solv- ing inverse problems in intraoperative imaging.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Fast auto- differentiable digitally reconstructed radiographs for solv- ing inverse problems in intraoperative imaging

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.500362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:a2e73844e7ce41774679339ce2e5717b38cd23133bb8b0a734e467ed1fed9ff9

Observation 75175b41-7784-4952-8ce8-f582ea5f5c02 · outbound

This paper cites A robust method for reg- istration of three-dimensional knee implant models to two-dimensional fluoroscopy images.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A robust method for reg- istration of three-dimensional knee implant models to two-dimensional fluoroscopy images

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.460526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:8f50e176da5840c0d58f6da608dc20701e3c492cb0cb16650b7856f82e797d02

Observation 78f9b35d-adf4-4c48-994b-3a9960ce64cd · outbound

This paper cites In vivo measurement of 3-d skeletal kinematics from sequences of biplane radiographs: application to knee kinematics.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration In vivo measurement of 3-d skeletal kinematics from sequences of biplane radiographs: application to knee kinematics

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.306739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:b34be8a35358357c0688013d8f982094d296effffdbc1fb2f30852082c1458e2

Observation 8ac8da08-474e-43cc-8866-93721aee4b01 · outbound

This paper cites Generalizing spatial transformers to projective geome- try with applications to 2d/3d registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Generalizing spatial transformers to projective geome- try with applications to 2d/3d registration

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.403530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:d9a66514152e493326b32fd1341509427a8232506eacbbe7998e1ce6ddf766fe

Observation 30fa65a4-1bcd-47b7-b998-9491869d6c66 · outbound

This paper cites Extended capture range of rigid 2d/3d registration by estimating riemannian pose gra- dients.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Extended capture range of rigid 2d/3d registration by estimating riemannian pose gra- dients

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.292373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:ece6e0a50dc4994d95a7571ce0769153cb45f76cbf9e7c62d37d1183360b7264

Observation 3ff390a4-0105-49f3-86c3-61108d18d25a · outbound

This paper cites A fully differentiable framework for 2d/3d registration and the projective spatial transformers.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A fully differentiable framework for 2d/3d registration and the projective spatial transformers

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.467988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:e219485ada9e2b9ce7ec41ae6f6d1a45913eb3568cd8a3a7959da3b703cce504

Observation ae868a57-e9e9-45d5-992c-f0600a833276 · outbound

This paper cites A review of 3d/2d registration methods for image-guided interventions.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A review of 3d/2d registration methods for image-guided interventions

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.324598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:70a8be7f65ba8aabbecdc91af3272197ae1ffe80d6fe156c92a75c557d5b11a4

Observation 04924cd9-710a-48e2-ae65-5196bd8a1c5d · outbound

This paper cites Pose estimation of periacetabular osteotomy fragments with intraoperative x-ray navigation.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Pose estimation of periacetabular osteotomy fragments with intraoperative x-ray navigation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.282288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:c1e501e755e62249ba77110114eba91ab7fb2af208bb8297e290f7f64b5709f3

Observation aa20c00d-dcfc-4509-b46f-b1046cb49d8d · outbound

This paper cites Learning to detect anatomical landmarks of the 20 pelvis in x-rays from arbitrary views.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Learning to detect anatomical landmarks of the 20 pelvis in x-rays from arbitrary views

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.303186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:01d668e8bb05db55271614c0b90abd1cf01f315994d97192ba234f8eab38ff4e

Observation 49916deb-9ec9-432f-a3b8-d7a9fb4ad0e1 · outbound

This paper cites Towards fully auto- matic x-ray to ct registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Towards fully auto- matic x-ray to ct registration

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.474725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:12863bf39277184a0be736cf6e4584f037173966f090e995946919d4aa40f718

Observation a84890a5-b2cd-47b8-ac93-e37a5c91cb76 · outbound

This paper cites X-ray to ct rigid registration using scene coordinate regression.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration X-ray to ct rigid registration using scene coordinate regression

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.435330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:7254d0044e66be6c4797c63baf0d8408e1771020ae7b256ceebc51b60177932b

Observation df69865f-0716-4127-bf45-fe2ce2bfe206 · outbound

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

Rapid patient-specific neural networks for intraoperative X-ray to volume registration RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:15:12.812215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:3b9bd44069f8c634df7eec30e296877c9163b1d7c985cb761c8ca339db147fda

Observation a13253e5-c7af-43a1-87a8-5140186dcadf · outbound

This paper cites A cnn regres- sion approach for real-time 2d/3d registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A cnn regres- sion approach for real-time 2d/3d registration

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.442533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:aeb198614124d9fbf008fefa1e7ad5aa416d7ee9b4319a0d371f1cb9e86916eb

Observation 79427b14-d20c-429e-bed3-0a57c44f4bda · outbound

This paper cites X-ray posenet: 6 dof pose estimation for mobile x-ray devices.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration X-ray posenet: 6 dof pose estimation for mobile x-ray devices

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.420493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:b8038c9fc9cd3298f7ec9949844646854d35e5b610e2d5832b09cfeaec1ee2a3

Observation 487d8a10-9758-408b-bd27-d95928ee8fe9 · outbound

This paper cites A patient-specific self-supervised model for automatic x-ray/ct registra- tion.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A patient-specific self-supervised model for automatic x-ray/ct registra- tion

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.478987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:4f3db4009f7cf02fc06970cd89c85aa486c9e4249d825cc3d67d36307297ced8

Observation ca0a9a88-5933-47a3-9baa-3b6bc8305b52 · outbound

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

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:15:12.801580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:49014de616d34c4d71fb2e16e6eb7629a9cb3649b01ff7576a0fed3189ca0eed

Observation a3c09971-486f-4bdf-ad74-2d63f614dc1e · outbound

This paper cites Automatic annotation of hip anatomy in fluoroscopy for robust and efficient 2D/3D registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Automatic annotation of hip anatomy in fluoroscopy for robust and efficient 2D/3D registration

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.443307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:cf3e79385d53b3eece0510b66bd4c3f870e6485d18cd03fd43935d864de42973

Observation 759516c2-173d-4568-95af-1380190d94a0 · outbound

This paper cites Synthetic data accelerates the devel- opment of generalizable learning-based algorithms for x-ray image analysis.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Synthetic data accelerates the devel- opment of generalizable learning-based algorithms for x-ray image analysis

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.446723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:36334d0c6e249926185131b16383c7c4b12c70bfcccd70e466f3a1d56ed603b8

Observation 706cf1d9-5d6b-464d-aa2f-9360bdf8610e · outbound

This paper cites Fast calculation of the exact radio- logical path for a three-dimensional CT array.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Fast calculation of the exact radio- logical path for a three-dimensional CT array

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.489751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:8b240bc635287797100fdcc38da88c57ac49f825b48c08b53167731365e8edfa

Observation a080ae46-7d2e-4a44-947b-0a10a214f59b · outbound

This paper cites AI in health and medicine.Nature Medicine, 28(1):31–38.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration AI in health and medicine.Nature Medicine, 28(1):31–38

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.275220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:79263daea6229c420e1d3643bf20c46f24d7fb03dbaec4e0a49840bc912e6329

Observation d9528b99-d5eb-462b-9330-e7ed08a9969c · outbound

This paper cites Artificial intelligence in surgery.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Artificial intelligence in surgery

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.496660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:023494e6a1aa560d00500c561336c65f69156f38310ccc430fbfc6f46f8316fc

Observation 6ecdaacc-f870-41b2-a906-2f459dfc6750 · outbound

This paper cites Artificial intelligence meets medical robotics.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Artificial intelligence meets medical robotics

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.217370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:27c6e6939c45272c1c125d32ea7eeba263cecb2b1fe06c2774634572728f30d4

Observation c7b437f7-c9bc-423b-9e04-6c657849b9fb · outbound

This paper cites 3D-2D registration of cerebral angiograms: A method and evaluation on clinical images.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration 3D-2D registration of cerebral angiograms: A method and evaluation on clinical images

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.453301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:6d723f8070062fab392bfb16a55e7c05d9c0c6ee4abdd29fa4948705921c00fa

Observation b9881d15-9b5c-45af-b2d7-3c7353a22469 · outbound

This paper cites Deep learning to segment pelvic bones: large- scale CT datasets and baseline models.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Deep learning to segment pelvic bones: large- scale CT datasets and baseline models

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.233906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:29c3188ef274925700612039e46d97a2e8d3367908dee4f15796f3ad5668edf6

Observation d99e7128-1dc2-4bd6-a0ee-3bb993785d6e · outbound

This paper cites The ANTsX ecosystem for quanti- tative biological and medical imaging.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration The ANTsX ecosystem for quanti- tative biological and medical imaging

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.269852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:31013bc2a8380d239e9096de8b9c6de4b5c6409f91cc824e98474f77410a3fa2

Observation 91137645-bc24-4a75-9fdd-8c358d6f4d82 · outbound

This paper cites Mag- netic resonance angiography atlas dataset.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Mag- netic resonance angiography atlas dataset

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.310055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:c394440314cc8705e459cc935bdcdea0806dcbbb3be4d6e7c0fc830c0403f16b

Observation 4b6b06ba-a293-4b29-943c-608ea46d32be · outbound

This paper cites VesselBoost: A Python toolbox for small blood vessel segmentation in human magnetic resonance angiography data.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration VesselBoost: A Python toolbox for small blood vessel segmentation in human magnetic resonance angiography data

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.393277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:8dd32e91a8cce33ae5efcc004f91f3f996eef84b1c0ceb3f1488ab0978edd5d6

Observation 4ecd54ff-fe49-4fa8-83d3-18c9592a4b03 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Adam: A Method for Stochastic Optimization

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-05-22T23:15:12.807226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:85b62c0d8a50a6c93395a30a5f1867a137d4c5f6cfe1fce4ba23233b22bf7cfa

Observation 171ef6aa-d687-439d-a697-d2e43a0df278 · outbound

This paper cites U- net: Convolutional networks for biomedical image seg- mentation.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration U- net: Convolutional networks for biomedical image seg- mentation

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.373587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:de1af6f68d0bf3719cd8b94174e53ea47e88f1c4a08e474e56d7049600a5b0ed

Observation e189dc6b-c2f1-449f-86eb-b4d9bfa6e740 · outbound

This paper cites A robust O(n) solution to the Perspective-n-Point problem.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration A robust O(n) solution to the Perspective-n-Point problem

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.354275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:30b877dda9f3ce385933e44db21b53d9a5ae8ce9eb8de4f71604210d8d4c6f56

Observation bf746181-2813-419f-8833-9badf7e1495f · outbound

This paper cites Vascular hetero- geneity and specialization in development and disease.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Vascular hetero- geneity and specialization in development and disease

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.419232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:c975be4e038f3b7bb652ef589b3cd03c3d8f240db954d260680c09b6db370b71

Observation bfa843cb-20cf-4fb9-a8fb-c37c837c570f · outbound

This paper cites TotalSegmentator: robust segmentation of 104 anatomic structures in CT images.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration TotalSegmentator: robust segmentation of 104 anatomic structures in CT images

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.471551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:30a673195c209ea52028dd99cb394e425b60cfa6abcf32abda7016fbfadffa1a

Observation afaf99e8-a158-4bdc-8636-b48b25838604 · outbound

This paper cites Patch-based image similarity for intraoperative 2d/3d pelvis registration during periacetabular osteotomy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Patch-based image similarity for intraoperative 2d/3d pelvis registration during periacetabular osteotomy

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.371516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:9b3e3c2b13a8556d9184fe65958608419a4d3447c6d4c4bf93cbe1868ec45bc9

Observation 78f888ed-034b-4a84-8a48-6851c5d1355b · outbound

This paper cites Deep learning in medical image regis- tration: Magic or mirage? In The Thirty-eighth Annual Conference on Neural Information Processing Systems.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Deep learning in medical image regis- tration: Magic or mirage? In The Thirty-eighth Annual Conference on Neural Information Processing Systems

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.317853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:cb93c2bdb3742e8321c1d05b0fe7ae6d0165ea28def3b636f708423d78e3412a

Observation 59cd7a51-0799-440b-9b50-fd9f62deeaf5 · outbound

This paper cites an unresolved cited work.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-05-22T23:15:13.320706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:7d74615b8c54e68cf2a1c1fee9847f8ee88803b31be05ebcb1d8bfefc0fa0252

Observation a2c5242e-e2a8-4f80-b284-d7ef94a37e10 · outbound

This paper cites Convexadam: Self-configuring dual-optimisation-based 3d multitask medical image registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Convexadam: Self-configuring dual-optimisation-based 3d multitask medical image registration

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.323722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:139352a1824e872c33c09ac1f6a707f9d2def394156944b45598bab9c79017d8

Observation 043d8a15-ce79-4ac2-877e-f2341b16214e · outbound

This paper cites Wong, Clinton Wang, Mengwei Ren, Ellen Grant, Adrian V Dalca, and Polina Golland.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Wong, Clinton Wang, Mengwei Ren, Ellen Grant, Adrian V Dalca, and Polina Golland

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.326878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:1e1de84561c082929f76f2c40a637f5187169d4bad3918edda6e72e72aae599c

Observation ddbc5b13-ee88-476d-a243-60c9c498c32f · outbound

This paper cites Automated detection and reacquisition of motion- degraded images in fetal HASTE imaging at 3 T.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Automated detection and reacquisition of motion- degraded images in fetal HASTE imaging at 3 T

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.333359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:15664ef5056584d7fbffb34c79616390180b42e546bd7f49167419f74c9c942b

Observation 8cef86cd-ddc3-4b77-be6e-efc8610293e5 · outbound

This paper cites Demon- stration of an ai-driven workflow for autonomous high- resolution scanning microscopy.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Demon- stration of an ai-driven workflow for autonomous high- resolution scanning microscopy

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.406695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:b937c16a528f21f54cdb497b5c53533cf5a0349665edcb26f1936cba79a35337

Observation 656d727b-ad19-45a8-a7f6-d187b584d143 · outbound

This paper cites Model- agnostic meta-learning for fast adaptation of deep net- works.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Model- agnostic meta-learning for fast adaptation of deep net- works

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.344065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:d884c1de00cb8f41f2091d7d1a32f51ab37b9f6c0960a7111a63f9b110885c82

Observation dfe99739-a13d-4200-b383-7ca8bea2ff6d · outbound

This paper cites Deep equilibrium models.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Deep equilibrium models

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.417214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:efb5acc0c4410cdadeccb6311bcb91175e50b46e8dec5264aaa387e1cb2589fa

Observation b240b756-2477-4ee1-88ed-ebad3ae3834c · outbound

This paper cites Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:15:12.805799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:7a00f36a41940239d9c597b7c7a6989404e578b901e6f63a3a020be328b290ea

Observation 4b99ec10-db9d-4ce7-9472-0c5512820b92 · outbound

This paper cites Py- torch: An imperative style, high-performance deep learn- ing library.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Py- torch: An imperative style, high-performance deep learn- ing library

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.456510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:3bd9de75b22f5570e697130a7eeee8590a9f955e2b4de7933c2737ebaea79392

Observation 525eab60-8ee7-43e8-933c-df4b17d2ba4a · outbound

This paper cites Multiple view geometry in computer vision.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Multiple view geometry in computer vision

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.396244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:ce7e2315359f2bd93c748a2ca2b8df79688db47409400067c345560910825eae

Observation 8bba66fb-8bf4-4129-9ff0-0ab211a2a5c6 · outbound

This paper cites Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT Reconstruction.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT Reconstruction

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:15:12.796254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:e3ee7e7c78cb17103511eef360f4bc52f8bf1c0ea294771046fa03628eb96bdd

Observation c9cf65f0-1aa5-4c53-be02-e0f6b863fda1 · outbound

This paper cites Deep residual learning for image recognition.

Rapid patient-specific neural networks for intraoperative X-ray to volume registration Deep residual learning for image recognition

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T23:15:13.414015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T23:14:26.488603Z digest=sha256:27dc0b564a75e6569496e6b9b64f93eee1887cdaa99685897f87aad6641eb081

Pith citing papers

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

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:56:42.470631Z digest=sha256:69e1be83727d713668b04fa6b17f031833c0b2b58dfc8d57ef363e168dcca18d

Observation a83ef267-7d4f-46ab-818b-25cb4144c038 · inbound

Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration cites this paper.

Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration Rapid patient-specific neural networks for intraoperative X-ray to volume registration

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-31T23:43:51.917001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:43:51.917001Z digest=sha256:1ab340cdec6ef3ed14b4ad509206ac03deaa89efe29c5f46ce4f8d715d0ef0be