{"as_of":"2026-08-22T21:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1491bf89ea856aa77e0bba830739a7b81e1b53d99c1a0d8f98543d4058e5d1d0","coverage":[{"denominator":72,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":72,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T23:43:55.245805Z","state":"measured"},{"denominator":72,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":72,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.23343/citation-record","integrity":"/paper/2607.23343/integrity","json":"/paper/2607.23343/citation-record.json","paper":"/paper/2607.23343"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:48.590675Z","title":"In: International Work- shop on Computer-Assisted and Robotic Endoscopy, pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:48.590675Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:1f2d1807da27539cbf3363a79fea11016f8e7dedf9f3c1c7f2e94744699b827e","observation_id":"f457f0de-3949-4524-bc58-2dc8a9f48690","resolution":{"observed_at":"2026-07-31T23:43:48.590675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:48.688835Z","title":"IEEE transactions on medical imaging17(4), 586–595 (1998)","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:48.688835Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:f65c81a7b865e639e0cb4bf156be620219d81aaa9b4cded574a05c8f88d5d650","observation_id":"d7a96b97-9db4-4164-9c21-ba5f67836f4f","resolution":{"observed_at":"2026-07-31T23:43:48.688835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:48.787929Z","title":"In: International Con- ference on Medical Image Computing and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:48.787929Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:76ac3a4cc0a4927033ed21d247c81b6ead444f2ca536477c73d717e80c2a634f","observation_id":"f4602cbd-daaf-4236-8d95-587e8ad25093","resolution":{"observed_at":"2026-07-31T23:43:48.787929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:48.828884Z","title":"Medical Image Analysis67, 101815 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:48.828884Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:4c9194e456ffe2b108c6b4db6b385b1e0cb9dcc35126002777496b0574195f7c","observation_id":"821d677a-69b2-44a6-9a57-f5e1ffd7a91b","resolution":{"observed_at":"2026-07-31T23:43:48.828884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:48.905083Z","title":"Physics in Medicine & Biology61(8), 3009 (2016)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:48.905083Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:052d337d53f64eda37b72c0e05f913b04a54066cbee9ffad7b1e4398db1387a0","observation_id":"5c482db8-ee7d-4fb8-9b53-2e464cff20da","resolution":{"observed_at":"2026-07-31T23:43:48.905083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.078543Z","title":"Medical image analysis16(3), 642–661 (2012)","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.078543Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:4395866640722e3a204523b8136c7be849d5953b2cf6b6c33931a3bb1569a6e5","observation_id":"a91cfef1-8d00-4f0d-8e65-d3b3b06a4e67","resolution":{"observed_at":"2026-07-31T23:43:49.078543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.193857Z","title":"In: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), pp","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.193857Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:4ab7f626a334f4b06edf7abdafe2dc55dfda899c2738b8acef925d4e172c8218","observation_id":"5c0ebea4-1578-4cc9-bf14-4f45ac0961a5","resolution":{"observed_at":"2026-07-31T23:43:49.193857Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05642","last_updated":"2024-08-19T00:54:29Z","snapshot_observed_at":"2026-08-16T14:20:15.080107Z","submitted_at":"2024-02-08T12:56:26Z","title":"An Optimization-based Baseline for Rigid 2D/3D Registration Applied to Spine Surgical Navigation Using CMA-ES","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05642","snapshot_observed_at":"2026-07-31T23:43:49.310826Z","title":"arXiv preprint arXiv:2402.05642 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.310826Z"},"links":{"cited_paper":"/paper/2402.05642","citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:2525504238856701059c1cb1ec7cb058e64b6721d8ed3765c1877756631979be","observation_id":"8bd1c12f-c282-44c6-8676-41193c4cf7b5","resolution":{"observed_at":"2026-07-31T23:43:49.310826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.427146Z","title":"IEEE transactions on medical imaging37(1), 262–272 (2017)","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.427146Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:59826662defdba50657998a50b06df052f2f1182a7d1e0936c67f809c6e2ad45","observation_id":"2a580393-a589-43b8-a058-f64948059a2f","resolution":{"observed_at":"2026-07-31T23:43:49.427146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.543759Z","title":"Cambridge NA Report NA2009/06, University of Cambridge, Cam- bridge26, 26–46 (2009)","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.543759Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:f198bcb0bb10de3a60c41ca1f85a3f72d7ec6a956f7e3167e92d9c1a67506192","observation_id":"c3590ba7-ce52-4d54-bff0-2f930bdfd46d","resolution":{"observed_at":"2026-07-31T23:43:49.543759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.660280Z","title":"Evolutionary computation9(2), 159–195 (2001)","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.660280Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:5d44a505dcd19ba81b05b60ec864db33941da875fc3d7f1b291f4bdc96546785","observation_id":"c82979d3-d6ad-42b8-b885-9bf72cd652ec","resolution":{"observed_at":"2026-07-31T23:43:49.660280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.781207Z","title":"Medical Physics52(7), 17896 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.781207Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:fca5b14b667bf21bd574fd61d76493854a6ba0fa353c6e235c4a1c4895972dc7","observation_id":"5012fee8-b97f-4f85-82ba-57f373b7ef27","resolution":{"observed_at":"2026-07-31T23:43:49.781207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:49.931577Z","title":"IEEE transactions on medical imaging 35(5), 1352–1363 (2016)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:49.931577Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:228d1096adcce060bcee344050042a06ea6be5c9aace3d6d51e94f63c8b5d566","observation_id":"0c6b39de-42b8-40c2-964f-c6216dfb1afb","resolution":{"observed_at":"2026-07-31T23:43:49.931577Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.076662Z","title":"In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.076662Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:d6dae119ac575c8101535130a492cdb5d04e096b79346165eaa9d6c7469b1587","observation_id":"08edddf7-ced5-45bf-b3c5-5766e9f1b33c","resolution":{"observed_at":"2026-07-31T23:43:50.076662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.156507Z","title":"Biomedical Signal Processing and Control95, 106384 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.156507Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:f09bd28a5a05fc262b1189810d9bf49a35e84237838a5c56f9e517ba858ad176","observation_id":"1b48bf5c-21a3-4e85-b541-c064192edf97","resolution":{"observed_at":"2026-07-31T23:43:50.156507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.222648Z","title":"In: Interna- tional Conference on Medical Image Comput- ing and Computer Assisted Intervention, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.222648Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:23faa58047bea51304a692ee34a04b2b0482c1d2517ad7d668adbdd3811b0d25","observation_id":"9d45eac7-7a58-4618-ba82-6f8aac62a4b8","resolution":{"observed_at":"2026-07-31T23:43:50.222648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.321209Z","title":"IEEE transactions on medical imaging40(9), 2221–2232 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.321209Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:2dde8f26672b3a3b93c25200f05977bcdfc8bc82a9624795fabcfbf5fa33a5bb","observation_id":"931a66d1-be1a-4c8a-bddb-8906ab72d899","resolution":{"observed_at":"2026-07-31T23:43:50.321209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.423800Z","title":"In: International Workshop on Biomed- ical Image Registration, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.423800Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:e1e1d47bd3ab46f6a2dfbffe0e41a73b15de18deb3f3740ae7139d07286b979c","observation_id":"29eab8b9-155e-4b93-aa09-30a6091291fe","resolution":{"observed_at":"2026-07-31T23:43:50.423800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.492992Z","title":"In: International Conference on Medi- cal Image Computing and Computer-assisted Intervention, pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.492992Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:d1333e12fbf543da3eba376ef731d82d95724d14d040f14aff214cd706bbb028","observation_id":"ae1fbada-84dc-4dc0-b06d-305586789ea9","resolution":{"observed_at":"2026-07-31T23:43:50.492992Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.538870Z","title":"In: Interna- tional Conference on Medical Image Comput- ing and Computer Assisted Intervention, pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.538870Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:76e49df102a2f75be3b0ad6f269b5b24e9d8773d14873b9fbb0348049f87e2a2","observation_id":"a770a021-dced-4c55-bd9d-57358a361ec8","resolution":{"observed_at":"2026-07-31T23:43:50.538870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.642497Z","title":"In: Proceedings of the IEEE/CVF Winter Con- ference on Applications of Computer Vision, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.642497Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:826307ee2918241e59bc6a06b48a93b54c3a2db31a2bfd09a27f54ef01afa617","observation_id":"ddc21a7a-c85a-4040-b141-0cd76bc6b2b8","resolution":{"observed_at":"2026-07-31T23:43:50.642497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.723525Z","title":"In: Proceed- ings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.723525Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:1832c3aaaa5727ef6fecb270dbb02ed3b96b630759dd3c6182dd181c56f73545","observation_id":"9b1cc562-9366-484b-b04c-9e18d71cc2ea","resolution":{"observed_at":"2026-07-31T23:43:50.723525Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.804681Z","title":"In: International Conference on Medical Image Computing and Computer Assisted Intervention, pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.804681Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:710e9dffcc87849b8448ff4eca735d7e37e8c052204ac48a170b3b5bfa03fedf","observation_id":"1862805b-1d7a-4878-84fa-7b1b32c149b7","resolution":{"observed_at":"2026-07-31T23:43:50.804681Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.880766Z","title":"IEEE transactions on medical imaging (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.880766Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:526da4f7ea4f111330a5287cc5a4d6904c6898b8c60ed5f98b7a0a2c734da865","observation_id":"dc3b3b84-b3fd-4064-a8b8-2fb768c5439a","resolution":{"observed_at":"2026-07-31T23:43:50.880766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:50.970845Z","title":"In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI), pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:50.970845Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:777d649236a9d6c5ae992adcdc82710762ba861bd2c63b55fcef444890dba722","observation_id":"00415d88-5a7c-453d-936c-46772b435d43","resolution":{"observed_at":"2026-07-31T23:43:50.970845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.021605Z","title":"In: ICASSP 2024-2024 IEEE International Con- ference on Acoustics, Speech and Signal Processing (ICASSP), pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.021605Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:7477a961d60f0d4078ae5d99fa27bebfa676f2727cce959333bbc94d0b554bf2","observation_id":"22da4b81-19f2-44d6-a82b-3f033f327965","resolution":{"observed_at":"2026-07-31T23:43:51.021605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.077211Z","title":"In: Interna- tional Conference on Medical Image Comput- ing and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.077211Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:d265e7551b11dabd892d7f71e11b7e41f9f2cff2073cad0e49a7e4d0e1d8748d","observation_id":"27f9f787-4e35-4a7d-b1a6-9e490f2559f8","resolution":{"observed_at":"2026-07-31T23:43:51.077211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.137074Z","title":"In: Proceedings of the IEEE/CVF Winter Conference on Applications of Com- puter Vision, pp","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.137074Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:acf56eb6361c99514ad6183baea3e2f4e742ebbf64573c86190ca2b28b7e8f3c","observation_id":"af5a8879-f07e-4224-8f07-67457a74e6c2","resolution":{"observed_at":"2026-07-31T23:43:51.137074Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.212077Z","title":"In: International Con- ference on Medical Image Computing and Computer Assisted Intervention, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.212077Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:e5625f64ed1c844de009472b147f8b1b366416ec41e3e189b23eb4b4a3fffd9b","observation_id":"cfc92e35-c064-4cac-af6c-50623429a009","resolution":{"observed_at":"2026-07-31T23:43:51.212077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.281601Z","title":"In: 2016 IEEE 13th International Sym- posium on Biomedical Imaging (ISBI), pp","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.281601Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:683a38a0415fc260f6eaef0f56bafed4b27c30b535cbc83c5c90f8e11ad1c229","observation_id":"cecf6353-4881-4aa2-aa17-6953766eda72","resolution":{"observed_at":"2026-07-31T23:43:51.281601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.339259Z","title":"In: In Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.339259Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:d588b69ab8fb8e3830468b2d6f9c791681e39ef7fab3671020a812d2416c64fb","observation_id":"c6cb78fd-9fa6-4202-b678-2248876e03e0","resolution":{"observed_at":"2026-07-31T23:43:51.339259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.421267Z","title":"In: Inter- national Conference on Medical Image Com- puting and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.421267Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:39ce11ff94e06fed33d94c51b6ac9b4ae8712e0dd10e1f2ac6915b8180c649b5","observation_id":"471d45bc-1d98-44ca-b686-613c1e5f80f0","resolution":{"observed_at":"2026-07-31T23:43:51.421267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.472290Z","title":"In: Proceedings of the Asian Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.472290Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:6d8de2bb327b146ce377a0e4f7365efb7290feaa47158848b55e5ff423ec0c44","observation_id":"608a03be-7b15-4ca2-8303-7be34b63db31","resolution":{"observed_at":"2026-07-31T23:43:51.472290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.526327Z","title":"IEEE transactions on pattern analysis and machine intelligence34(7), 1444–1450 (2012)","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.526327Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:efef4296a49379f3cb91ee6fe0bc0a2cb3d6df462d83700cac2e6a585aa3c5f5","observation_id":"6be7833a-8da3-46e7-8494-b97b52e65088","resolution":{"observed_at":"2026-07-31T23:43:51.526327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.582735Z","title":"In: International Conference on Medical Image Computing and Computer- Assisted Intervention, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.582735Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:5d4495376ed912fa141f570a60813baf156a20b32c1833318b08d690dee9dac9","observation_id":"ec263d57-85cd-4a8e-bede-e02562666b8b","resolution":{"observed_at":"2026-07-31T23:43:51.582735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.636597Z","title":"IEEE transactions on medical imaging39(10), 3159–3174 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.636597Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:c0af1f5e6b1bb2b11b5e5715c24a952dff745f20025c27ac9487ceb4b9fc0cad","observation_id":"6c607adf-2845-4ef0-bc0c-1cfad7f1bd41","resolution":{"observed_at":"2026-07-31T23:43:51.636597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.696675Z","title":"IEEE transactions on medical imaging 36(9), 1939–1954 (2017)","venue":null,"work_id":null,"year":1939},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.696675Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:012144da418d03c1ae9377efb12040110f0d783d828304db0177364af3d4654b","observation_id":"09c5777b-af00-4fcd-bf79-0d9a81a0db97","resolution":{"observed_at":"2026-07-31T23:43:51.696675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.766828Z","title":"Communications of the ACM24(6), 381–395 (1981)","venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.766828Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:2e62c54e9da4630b34faae2f3db0920893ddce494a3687fc4dcf7f118bb5d1b1","observation_id":"63ab27a0-3121-4376-8c39-a64f02a63417","resolution":{"observed_at":"2026-07-31T23:43:51.766828Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.843131Z","title":"International Journal of Com- puter Assisted Radiology and Surgery, 1–10 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.843131Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:ac8a3b3c02850063ad2abf1911e84d0ba4c485397eba43cbd70d1e2879b33752","observation_id":"d695c219-2c98-4fb4-97d0-72155cdc6618","resolution":{"observed_at":"2026-07-31T23:43:51.843131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.16309","last_updated":"2026-05-19T15:47:49Z","snapshot_observed_at":"2026-08-20T06:35:53.935697Z","submitted_at":"2025-03-20T16:33:45Z","title":"Rapid patient-specific neural networks for intraoperative X-ray to volume registration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.16309","snapshot_observed_at":"2026-07-31T23:43:51.917001Z","title":"https://arxiv.org/abs/2503.16309","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.917001Z"},"links":{"cited_paper":"/paper/2503.16309","citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:1ab340cdec6ef3ed14b4ad509206ac03deaa89efe29c5f46ce4f8d715d0ef0be","observation_id":"a83ef267-7d4f-46ab-818b-25cb4144c038","resolution":{"observed_at":"2026-07-31T23:43:51.917001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:51.993749Z","title":"In: Workshop on Clinical Image-Based Procedures, pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:51.993749Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:e89caa816be2e6c82cd8eae0bc3520a4be4890f728bb37df7d09cd5baec52d47","observation_id":"d99cb6de-4d87-4d66-8816-54959ddbd0f0","resolution":{"observed_at":"2026-07-31T23:43:51.993749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.069831Z","title":"In: 17 International Conference on Medical Imag- ing with Deep Learning, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.069831Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:f819e93ccb8ceed6d51fd8cf849b9c45260fd00bda5af5a3e17df2a48adc4d42","observation_id":"b73a68a2-a6cf-4ce3-99eb-5da1bc6fa22d","resolution":{"observed_at":"2026-07-31T23:43:52.069831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.153273Z","title":"Imaging Neuroscience2, 2 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.153273Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:a626b1b2fcf4fe48b432f196251d8a2e339a6da37ab21248476a0708677186ad","observation_id":"ffd8dc34-3474-441e-a08a-d1b8633a2e51","resolution":{"observed_at":"2026-07-31T23:43:52.153273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.231271Z","title":"In: The Thirteenth International Conference on Learning Representations (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.231271Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:cad8161b61c811ef8794c15459a35fe29ec2a4c45e1b71c3a1365c165488ecb2","observation_id":"e3a79a0b-a7b9-4338-a549-53790ea73cb4","resolution":{"observed_at":"2026-07-31T23:43:52.231271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.308385Z","title":"Medical Image Analysis105, 103669 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.308385Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:4ebe7d772174cd0da31bd5ed387c9fa567f77731c6c7f26a7de576ed71440f96","observation_id":"462261f8-470b-4244-9d49-c78f9d22ee64","resolution":{"observed_at":"2026-07-31T23:43:52.308385Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.383731Z","title":"Medical Image Analysis86, 102789 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.383731Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:68152a59f1c5adadcfa29f7770c2c02a0aef3f6ae566c56f2dadf1eb589fb6e6","observation_id":"b8132e1f-6ec5-469b-a6d4-40f4e762b9e5","resolution":{"observed_at":"2026-07-31T23:43:52.383731Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.460588Z","title":"Proceedings of the National Academy of Sci- ences120(9), 2216399120 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.460588Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:98cf96d715dd86642ca6b235dd6d4ca61876c5091c7a71ce2b8a5377250e39c6","observation_id":"01daed7b-5ac1-4859-afcb-b11b1f7004cc","resolution":{"observed_at":"2026-07-31T23:43:52.460588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.539893Z","title":"In: 2024 IEEE International Sympo- sium on Biomedical Imaging (ISBI), pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.539893Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:280fab82b6593a724d0706aaf68ed9f2c70326acb347e5b13d3870ec1adc00b4","observation_id":"057b73b0-cf9e-4a31-8643-8ac792af0697","resolution":{"observed_at":"2026-07-31T23:43:52.539893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.624722Z","title":"NeuroImage260, 119474 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.624722Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:b6cdb4360c3d3958554742c7c58d28d104662020d9eceff07150a4c51a9ea221","observation_id":"0d09c456-5cf7-46f7-910f-d676885e90cd","resolution":{"observed_at":"2026-07-31T23:43:52.624722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.674499Z","title":"IEEE Trans- actions on Medical Imaging41(3), 543–558 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.674499Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:61721f1821b0e9a1702d7d4db9ef652c5c74087f3afc9b9edeae0f9c62e4e26b","observation_id":"aa3499f8-1701-4933-934a-dc23306346a6","resolution":{"observed_at":"2026-07-31T23:43:52.674499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.813802Z","title":"Imaging Neuroscience2, 1–33 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.813802Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:760e7863f3efa76bad186d6d21c8824895d8f60db7b08696ab215b7c391a0211","observation_id":"f535311d-3c46-4ac4-bcc8-74437d32a3c6","resolution":{"observed_at":"2026-07-31T23:43:52.813802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:52.979165Z","title":"International journal of computer assisted radiology and surgery14(9), 1517–1528 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:52.979165Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:ae1b647ef716bb3b9a7d3d2891183928e749dc59db5ef3b11635c81321a3523a","observation_id":"8635c767-ec84-4b94-a1bf-fa6fe68ffdda","resolution":{"observed_at":"2026-07-31T23:43:52.979165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.089424Z","title":"Nature Machine Intelli- gence5(3), 294–308 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.089424Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:b0cccd87c01736963beb3329bdbe0fa7947ad8598d68d090d6c90df5e118badf","observation_id":"44ff4d40-3242-4424-a15c-0f3544725fa8","resolution":{"observed_at":"2026-07-31T23:43:53.089424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.201268Z","title":"Interna- tional Journal of Computer Assisted Radiol- ogy and Surgery19(5), 939–950 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.201268Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:454191e59be4a0b191162e56ae96c96f0c36195d8471003bce90b40fbf6c7105","observation_id":"ae7d9cbc-7cb7-433e-a274-5806d1bba124","resolution":{"observed_at":"2026-07-31T23:43:53.201268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.306800Z","title":"In: European Con- ference on Computer Vision, pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.306800Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:14b2014a003acdb0c323a7cf130d0b7fbb997f9ccfeea40edcdd8271a019a0a3","observation_id":"f5a2ad11-f4b8-4d4c-8fa9-4ec8b2080c5a","resolution":{"observed_at":"2026-07-31T23:43:53.306800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.382484Z","title":"In: Interna- tional Conference on Information Process- ing in Medical Imaging, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.382484Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:46c9ab1f038720b96855cc805f924901337c719a3768cb6c1a37ae51e2837b14","observation_id":"16683e2a-fab1-411b-92d9-1e275430db40","resolution":{"observed_at":"2026-07-31T23:43:53.382484Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.459122Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.459122Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:0a7a375bd749b74dab78d62bbd4324429e1e29303d66ec0f8f81ca2e6eecfd61","observation_id":"0fe12156-920f-437d-952a-84df5cbf7387","resolution":{"observed_at":"2026-07-31T23:43:53.459122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.545621Z","title":"In: International Conference on Medical Image Computing and Computer- Assisted Intervention, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.545621Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:b57829822475706a50b9334b6e5d5167aea9865314159b4b2f1c680031a0e21d","observation_id":"55ea4104-aa98-4604-bb96-ee3840729b00","resolution":{"observed_at":"2026-07-31T23:43:53.545621Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.599378Z","title":"In: International Workshop on Biomedical Image Registration, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.599378Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:d152295d23a2a9b1745ade6ffa16424f9ddbb2ab9b2988a0dc9785b3efe6f6ab","observation_id":"31331608-4c91-4880-b399-0f5f902d3a31","resolution":{"observed_at":"2026-07-31T23:43:53.599378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.634600Z","title":"In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.634600Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:590b58104fa9841c94c94bb12c9a7f0b3cc1412a1171008a2a12dd69fc845add","observation_id":"d95cfe26-27bb-4a43-8568-07a8e8df0b92","resolution":{"observed_at":"2026-07-31T23:43:53.634600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.828680Z","title":"In: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.828680Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:9a6be17876d3a3035348c7c09e971513e321566c9fc660861fd6b53c11e947e6","observation_id":"4aaabd92-42c8-428f-a575-caaed972dbf3","resolution":{"observed_at":"2026-07-31T23:43:53.828680Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:53.954650Z","title":"In: Machine Learn- ing in Medical Imaging: 11th International Workshop (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:53.954650Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:58ccbbde05058d685e6c8d7537f4cf762c5074b0b7657b2d2162469d58567a7c","observation_id":"8a639936-bb66-4586-8cb2-caabeacfa2af","resolution":{"observed_at":"2026-07-31T23:43:53.954650Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.095117Z","title":"IEEE transactions on medical imaging (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.095117Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:822fee5fd1e705cd34f300a14d6e01c40580a0002cda6f669043e659a65b8bc3","observation_id":"836a51bd-cf7e-4850-bf81-272491bb3240","resolution":{"observed_at":"2026-07-31T23:43:54.095117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.190826Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.190826Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:626fb81676604d3037338126c698253ef004740cdebd1a6e3860a95d0397bac4","observation_id":"1234eaf7-cb27-4e2e-b11f-7b9a0d80ec0b","resolution":{"observed_at":"2026-07-31T23:43:54.190826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.359821Z","title":"In: 2017 IEEE Winter Conference on Applications of Com- puter Vision (W ACV), pp","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.359821Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:b2bad2b53935c03202bfb641a59583849d669f44f91cfbd0d3a8fbbfb4c23275","observation_id":"e5e01a5e-7bf3-45d0-8d14-346fbb904261","resolution":{"observed_at":"2026-07-31T23:43:54.359821Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.488439Z","title":"International jour- nal of computer assisted radiology and surgery15, 759–769 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.488439Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:9e462072631e3242252e163585ce8a03ebf3b0a788b872f8cfc7cf63951a81f7","observation_id":"25910960-e155-4c74-9cd9-bae1ff528c46","resolution":{"observed_at":"2026-07-31T23:43:54.488439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.627976Z","title":"IEEE Transactions on Medi- cal Imaging32(8), 1550–1563 (2013)","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.627976Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:b9dfad5c48866fa9a446425a859a6216b80edef51d4b220332b5ba3ab6549111","observation_id":"bbe61873-5db4-4432-9b2a-1d4ab975064d","resolution":{"observed_at":"2026-07-31T23:43:54.627976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.763774Z","title":"Machine Learning and the Physical Sciences, NeurIPS 2024 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.763774Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:9732d87371eeab8434ec8347c321d18fd2c7bbab4437c10be2201d805edb9b22","observation_id":"f17f1e37-1b48-4de8-b85f-673b5d38592a","resolution":{"observed_at":"2026-07-31T23:43:54.763774Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:54.886028Z","title":"Medical physics12(2), 252–255 (1985)","venue":null,"work_id":null,"year":1985},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:54.886028Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:079173248003d58d43de19169109fdba458cf7940da8109377955ea6cb7c4997","observation_id":"cbd477d0-d6a5-4753-b371-3cd12e45ffb7","resolution":{"observed_at":"2026-07-31T23:43:54.886028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:55.015959Z","title":"IEEE Transactions on Biomedical Engineering (2026)","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:55.015959Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:0b0b000a36ccf6939d03f0c10018eab6e4deb27a0ea5e3da4bc7ca8b52adbcb8","observation_id":"1d5c97e8-103c-481a-b6ba-c116d7bb0bc9","resolution":{"observed_at":"2026-07-31T23:43:55.015959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:55.131356Z","title":"In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:55.131356Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:f733bb33d0be09fe57a475e2df0262128b21df2e934ee4fd275c64612c9bc2dd","observation_id":"fe0ece3b-ceab-4ad0-8b6f-6281710617c8","resolution":{"observed_at":"2026-07-31T23:43:55.131356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T23:43:55.245805Z","title":"Medical Image Analysis98, 103310 (2024) 20","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-07-31T23:43:55.245805Z"},"links":{"citing_paper":"/paper/2607.23343"},"observation_digest":"sha256:6b7eb60503f8b02447e5ae5b4ed34f39c0edf1e40e8d5536b0e7fc1920400a8f","observation_id":"0d35d770-bdf5-4e08-b725-851a435858e1","resolution":{"observed_at":"2026-07-31T23:43:55.245805Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.23343","last_updated":"2026-07-25T19:39:54Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-14T00:40:34.864798Z","submitted_at":"2026-07-25T19:39:54Z","title":"Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration"},"reference_resolution":{"displayed":72,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":72,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":72},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2607.23343."}