{"as_of":"2026-08-08T04:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:04fd5c4b972b23372d92034de2f6c4afd0156969aadd7a22b9b47f2baecc6894","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:01:11.648102Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2506.03804/citation-record","integrity":"/paper/2506.03804/integrity","json":"/paper/2506.03804/citation-record.json","paper":"/paper/2506.03804"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6203.25665","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:16.316946Z","title":"Positron emission tomography: An overview,","venue":null,"work_id":"5819358f-4fca-4f75-8256-d43893a9cc71","year":2006},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.598176Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:592546968cfccbca430b347800f91df5e6ccd218ffd017093453eb2b31ec991c","observation_id":"f75a4bf2-3667-4b64-83c4-6c59feed73ff","resolution":{"observed_at":"2026-08-07T11:01:16.324025Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00330-012-2447-9","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:13.323863Z","title":"Radiation exposure and mortality risk from CT and PET imaging of patients with malignant lymphoma,","venue":null,"work_id":"f7e047a7-49cd-41a9-bb4a-78f568b8296a","year":1946},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.629609Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:4d1484240190970125d6392dea63da2e321fb272662a86dab120c9264cfdc423","observation_id":"cc39e842-1652-4ea9-8ecc-4a24e1e5060d","resolution":{"observed_at":"2026-08-07T11:01:13.372286Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:16.337262Z","title":"PET/CT: Challenge for nuclear cardiology,","venue":null,"work_id":"d2bc619a-c827-4f18-9530-130a4e493870","year":2005},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.697632Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:3d334673cf478662ab6fe5cbd8c6d866f16ede50c4d99e12c93d357ce133a55c","observation_id":"45d3e62f-69d9-4721-977a-376f240410bd","resolution":{"observed_at":"2026-08-07T11:01:16.341530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2217/iim.10.49","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:13.174875Z","title":"Image reconstruction for PET/CT scanners: Past achievements and future challenges,","venue":null,"work_id":"3bea8dc8-5899-4673-9f26-a54e344dff9f","year":2010},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.760841Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:905c9ebbdaadf5bd31219e6d545761868b6725e92365e486309151ae4fbeb4fc","observation_id":"c3b29938-c53a-4ea9-8023-08b94e74aae7","resolution":{"observed_at":"2026-08-07T11:01:13.270422Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1053/j.semnuclmed.2012.08.006","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:13.006931Z","title":"MR guided PET image reconstruction,","venue":null,"work_id":"87b98548-f5f6-42cc-9e60-49e577f09a53","year":2013},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.845790Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:0de665f615328322bcc85ec41e75c51c8f44e21cf7f3357378a9d7870976eaf1","observation_id":"5f1a2f27-6c07-4c08-a16f-4ad5027f82e0","resolution":{"observed_at":"2026-08-07T11:01:13.111436Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:08.897579Z","title":"Syn-Net for syn- ergistic deep-learned PET-MR reconstruction,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.897579Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:b7a432721b14ab311263741c644ec6fbdeb463ee29d08f4b9b37d2d225900170","observation_id":"05a6c8f8-b6a6-417d-8531-3da58db96a3d","resolution":{"observed_at":"2026-08-07T11:01:08.897579Z","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":"2026-08-07T11:01:08.967597Z","title":"Score-based diffusion models for accelerated MRI,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:08.967597Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:980b8816be62df7ab70427bde7189e2431cabbd7f747be5e07fd12952f621af5","observation_id":"60ec4c48-ce12-4102-b481-100a4f82eaa1","resolution":{"observed_at":"2026-08-07T11:01:08.967597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05754","last_updated":"2024-02-19T14:34:59Z","snapshot_observed_at":"2026-07-06T15:01:10.693654Z","submitted_at":"2023-03-10T07:42:49Z","title":"Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05754","snapshot_observed_at":"2026-08-07T11:01:09.018800Z","title":"Decomposed diffusion sampler for accelerating large-scale inverse problems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.018800Z"},"links":{"cited_paper":"/paper/2303.05754","citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:da7dfd8f909784c4540754eaccdde893d7e9a0879a0caf0aee01282f95c945dd","observation_id":"2584e5b1-23a9-499f-abca-1b9e5a13a4e2","resolution":{"observed_at":"2026-08-07T11:01:09.018800Z","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":"2026-08-07T11:01:09.090359Z","title":"Score-based generative models for PET image reconstruction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.090359Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:4ad3418b90a498187546d019e266378988051f4178c54df3fb3ec6dbf6c97310","observation_id":"3c8e7e83-27ab-471c-814a-d14560068b36","resolution":{"observed_at":"2026-08-07T11:01:09.090359Z","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":"2025.35764","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:16.044462Z","title":"Likelihood-scheduled score-based generative modeling for fully 3D PET image reconstruction,","venue":null,"work_id":"e1afbce4-901f-42b7-847c-7919674518e6","year":2025},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.149761Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:495270d2dfa81aefd214bb932ce821eedd6ce1a504fc1924bd78cb0645e4e240","observation_id":"6ed65cc2-42f5-4455-97bd-3035eb816cec","resolution":{"observed_at":"2026-08-07T11:01:16.054678Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.30147","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:15.942651Z","title":"Deep learning for PET image reconstruction,","venue":null,"work_id":"9f6167d0-704e-4686-b15f-b28eae9543d8","year":2021},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.210772Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:5f22b13e24689ad1358cf04146032c790bc10ba715c38bc46e538a16333e6e67","observation_id":"ae916555-6d5b-48dc-8f29-e3917f9e68c1","resolution":{"observed_at":"2026-08-07T11:01:15.950653Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1982.43075","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:15.846122Z","title":"Maximum likelihood reconstruction for emission tomography,","venue":null,"work_id":"db5c0e7b-92b4-4df9-af0c-ef4032597cbb","year":1982},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.271162Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:4b9c0abc43abad550b4849ff72b4e0a36909baa979efbedc1aa7cf8aa51056b3","observation_id":"bf0ab410-723c-4d63-83d9-5761d01a4765","resolution":{"observed_at":"2026-08-07T11:01:15.853637Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1987.43078","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:15.758444Z","title":"A maximum a posteriori probability ex- pectation maximization algorithm for image reconstruction in emission tomography,","venue":null,"work_id":"c22c0310-c5a6-4df6-8b90-cf55b6e334f5","year":1987},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.354230Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:6b0ad6686aa1589a231485b0fa2f9838fb799c2d054334e282d4c092fcbfde69","observation_id":"5411647c-835d-4ff8-8e76-2f4124b98f57","resolution":{"observed_at":"2026-08-07T11:01:15.765752Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/42.363108","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:12.819697Z","title":"Accelerated image reconstruction using ordered subsets of projection data,","venue":null,"work_id":"88d28a49-01ad-4dd2-b30d-2704caaef766","year":1994},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.423761Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:7a0132128ff1f48420163b2eb24669985a2330cc34617fb5a94097250bedbdae","observation_id":"becc4af6-a143-4b39-9500-c7f3a0ea5369","resolution":{"observed_at":"2026-08-07T11:01:12.910915Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/42.921477","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:12.634751Z","title":"Fast EM-like methods for maximum","venue":null,"work_id":"b2932adf-0755-49a0-addf-551beb8bb25f","year":2001},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.492410Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:b2b57612a889743fceb366be880d9efe3c2b17b9d6f262e751aae19b57346f15","observation_id":"545b20a2-ac43-4b8d-a2fd-d41a5a29efa7","resolution":{"observed_at":"2026-08-07T11:01:12.732473Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.14627","last_updated":"2020-04-30T08:01:14Z","snapshot_observed_at":"2026-07-06T09:16:29.097337Z","submitted_at":"2020-04-30T08:01:14Z","title":"The convergence rate from discrete to continuous optimal investment stopping problem","version":1},"cited_work":{"arxiv_id":"2004.14627","doi":null,"metadata_source":"pith","pith_arxiv_id":"2004.14627","snapshot_observed_at":"2026-08-07T11:01:15.671469Z","title":"The convergence rate from discrete to continuous optimal investment stopping problem","venue":"q-fin.MF","work_id":"46b6a301-1a89-4344-82cd-898cea5c183d","year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.561497Z"},"links":{"cited_paper":"/paper/2004.14627","citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:04fa2b92dfa2f75cfe4dbf985e56d561e4bc1a203d4b52ca0977ff10dc803de4","observation_id":"82e87e69-942f-4f58-ba72-a60ad32eceeb","resolution":{"observed_at":"2026-08-07T11:01:15.676348Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2017.27679","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:15.645897Z","title":"Evaluation of parallel level sets and Bowsher’s method as segmentation-free anatomical priors for time-of-flight PET reconstruction,","venue":null,"work_id":"6774df70-95e7-442a-8a17-94abf391f504","year":2018},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.637998Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:a6678290e0ac1c99323549398d1d664b6adf31cde75bada01004b8a4994b4f60","observation_id":"65e79030-9077-47e2-bcdc-e4a6ca479421","resolution":{"observed_at":"2026-08-07T11:01:15.652885Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:09.726474Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.726474Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:0e62593c7edf70d0eda6e7ea732828a78ab1404b03850a99b4bb1c13b2c95565","observation_id":"1fe15da5-35df-441b-b5c2-c341dde2ca89","resolution":{"observed_at":"2026-08-07T11:01:09.726474Z","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":"5118.30453","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:15.463673Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics,","venue":null,"work_id":"9ae0a4d3-0e72-466b-87c6-1cc387444b0e","year":2015},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.807359Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:464d0f71e72786323bd670d3860fcfc14422733d1855b0d524502459aca66014","observation_id":"d9f2439a-dc73-460c-8d72-05cdecc25398","resolution":{"observed_at":"2026-08-07T11:01:15.471585Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:09.873080Z","title":"Improved techniques for training score-based generative models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.873080Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:95175145791608fe31584050045ded6b18e5e37856d24d72a39b69a6d7581c71","observation_id":"295f17da-7a05-46ce-916a-cb29cc5645f7","resolution":{"observed_at":"2026-08-07T11:01:09.873080Z","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":"2026-08-07T11:01:09.954334Z","title":"Solving 3D inverse problems using pre-trained 2D diffusion models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:09.954334Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:2fb1cd0a56d6cffd2517640a2814b81c2ec9b9b0a40054c5dfecc511d4ba5174","observation_id":"110a1a80-be03-4147-b58b-ccada550f5e1","resolution":{"observed_at":"2026-08-07T11:01:09.954334Z","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":"10.1093/bjrai/ubae013","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:12.468243Z","title":"Diffusion models for medical image reconstruction,","venue":null,"work_id":"be891971-eec5-4631-ac9f-63d1cda6cf7f","year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.041396Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:67e5ba8e0d28245d8b4884d84df9bb924d136b7fc8844cf29d02b43f1355858e","observation_id":"57f0fbd8-4a04-41cb-930b-ed694c32abe5","resolution":{"observed_at":"2026-08-07T11:01:12.547347Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.12598","last_updated":"2022-07-26T01:42:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-07-26T01:42:07Z","title":"Classifier-Free Diffusion Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.12598","snapshot_observed_at":"2026-08-07T11:01:10.132348Z","title":"Classifier-Free Diffusion Guidance,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.132348Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:2da93ad97a7d5cc78c51a770e17f8209d95b9e7056a5af82082e94282c10a70b","observation_id":"22ab915a-7025-4d0a-90f8-0f87d786ff81","resolution":{"observed_at":"2026-08-07T11:01:10.132348Z","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":"2026-08-07T11:01:10.222259Z","title":"V oxelMorph: A learning framework for deformable medical image registration,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.222259Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:e375c022f039fd18f5e15028e1cdc1ee22674958d456a7af89f01c928f18f422","observation_id":"8b0c50ba-2d79-410f-ac19-cd393f280a25","resolution":{"observed_at":"2026-08-07T11:01:10.222259Z","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":"2017.27714","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:14.935756Z","title":"MR-guided kernel EM reconstruction for reduced dose PET imaging,","venue":null,"work_id":"56a12ce9-5bc9-4b5d-8280-33ce16908fe4","year":2018},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.316329Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:1092466a638790370f2bac59c3dc891c039fdaf17b92aa7d81bae1188764ebbf","observation_id":"6ab46df7-b62f-490b-9136-8f4c558d728a","resolution":{"observed_at":"2026-08-07T11:01:15.036975Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:10.410128Z","title":"Model-based deep learning PET image reconstruction using forward–backward splitting expec- tation–maximization,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.410128Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:63c4d41ec0d17fb735d6b3f38480deb2260832d1ed640f71ecbea4c96dff62b1","observation_id":"51aebaed-1edf-4c60-a698-70b3f7069486","resolution":{"observed_at":"2026-08-07T11:01:10.410128Z","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":"10.1002/mp.15051","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Anatomically aided PET image reconstruction using deep neural networks,","venue":"Medical Physics","work_id":"df164bf7-3d0b-43a2-a81c-107686bd357a","year":2021},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.548627Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:0260efe55f5b9e2cb83d427e1e12709a474aa49764a4125264dd23fed8d2b878","observation_id":"11d45d78-c12a-44ef-9b64-169b99641989","resolution":{"observed_at":"2026-08-07T11:01:12.368536Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/1361-6560/aa7670","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:12.123590Z","title":"PET image reconstruc- tion using multi-parametric anato-functional priors,","venue":null,"work_id":"9b0c5c50-bb98-4681-87fc-7761fa06edf2","year":2017},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.631520Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:99b4b43bc77e2ef2943ba8464255bd05547b9c37c108c578e4264017a1737aac","observation_id":"06a8ef83-08e2-4520-bd75-d5e2fd65a5e3","resolution":{"observed_at":"2026-08-07T11:01:12.194862Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.29864","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:14.560201Z","title":"Micro-networks for robust MR- guided low count PET imaging,","venue":null,"work_id":"3732609e-ecf7-4449-80fc-b9d1835512d8","year":2021},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.731677Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:1202278e0f40923a70f78029d05a5a9e1b14713264a39e0c4c3bed279945b64b","observation_id":"a1ea2a17-4ec6-415a-b1e8-ef068a46bd11","resolution":{"observed_at":"2026-08-07T11:01:14.661511Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2018.28884","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:14.264741Z","title":"PET image reconstruction using deep image prior,","venue":null,"work_id":"a83f014f-2a84-48bd-9f9d-856c106875db","year":2019},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.815105Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:f0d67c03b8066f3fc4c5b6b2dd45f052833e3fb5f5d92b9b249b8ee53a06916e","observation_id":"a7df0143-437f-47ec-a3fa-7206a0507a45","resolution":{"observed_at":"2026-08-07T11:01:14.397764Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-319-24571-3","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Subject-specific models for the analysis of pathological FDG PET data,","venue":"Lecture notes in computer science","work_id":"c17911af-700f-4cff-bfc2-62c40634ca3f","year":2015},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.891732Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:18547f85e294633f9dea616940390fb020b17f76e1d14dbc9096308e38e4a9f3","observation_id":"c0e4774c-8f1a-4034-9144-60fa62fdf77a","resolution":{"observed_at":"2026-08-07T11:01:12.017934Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:10.975118Z","title":"Multi-subject image synthesis as a generative prior for single-subject PET image reconstruction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:10.975118Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:d85fc1835207f92ade13a31067c60ad52f7a6947b8c3f0c6471331368b289527","observation_id":"38d2dae7-395e-4927-86a8-1d22babd440f","resolution":{"observed_at":"2026-08-07T11:01:10.975118Z","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":"10.1117/1.jmi.1.2.024003","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:11.792101Z","title":"Global image registration using a symmetric block- matching approach,","venue":null,"work_id":"c2894d93-9b33-4a57-b012-52691dc52c96","year":2014},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.054099Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:3dd8cd3cb89c46780f01b7a3e55a9eb34354b2eb7d91a47c790dd4b6f8d29712","observation_id":"0f0c9911-d4a6-42eb-b4f4-dac65eafd9f0","resolution":{"observed_at":"2026-08-07T11:01:11.839939Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:11.151683Z","title":"Diffusion models beat GANs on image synthesis,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.151683Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:5257835e6cf157da7fac6854607d29c31f67b065d47628df9a607f8b74095c91","observation_id":"131ae5c8-62a1-4211-8049-8ce042a76c95","resolution":{"observed_at":"2026-08-07T11:01:11.151683Z","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":"2026-08-07T11:01:11.226001Z","title":"U-Net: Convolutional net- works for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.226001Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:3631973ecf86a9a4230715e4086c5694ee1391d05b54c9ceeaf361cc06194f31","observation_id":"e1be1791-8e42-45c0-aeb8-7c0f09dd9115","resolution":{"observed_at":"2026-08-07T11:01:11.226001Z","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":"2026-08-07T11:01:11.307946Z","title":"A connection between score matching and denoising au- toencoders,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.307946Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:a52c0e5d54b9dfe184ced097479ce569a118cb5fcb33c42e7fc34b63186db17c","observation_id":"02190f75-143c-4673-bf4f-6baf8f6aa259","resolution":{"observed_at":"2026-08-07T11:01:11.307946Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.13245","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:13.840546Z","title":"PARALLELPROJ—an open-source framework for fast calculation of projections in tomography,","venue":null,"work_id":"d363e95e-32fa-42ba-9d0c-871d445d993c","year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.389558Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:c15e6eec27136a71fdccd066dffa00221119db18ae3ed5a538d39f222248594e","observation_id":"f29e7a34-ffd4-4373-aaa9-700f6c3dc61d","resolution":{"observed_at":"2026-08-07T11:01:13.948677Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2019.29568","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:13.633988Z","title":"Bootstrap-optimised regularised image reconstruction for emission tomography,","venue":null,"work_id":"fe73fe18-b42a-4748-a503-4f06c05f9389","year":2020},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.480836Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:18d696d11586bbcde64b932792e004055506d1210f19721baa4802dcd8d24544","observation_id":"20acfde8-063d-40e7-9548-6edd06991ce5","resolution":{"observed_at":"2026-08-07T11:01:13.692607Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:11.565585Z","title":"Clinical and deep-learned evaluation of MR-guided self-supervised PET reconstruction,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.565585Z"},"links":{"citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:40a43c06cbc877e2bd914a57dfa69e1833d599239985ad4f10645d4ac2a4c72b","observation_id":"edcfda80-f25f-441b-8ff7-00472dd0dc03","resolution":{"observed_at":"2026-08-07T11:01:11.565585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.11730","last_updated":"2024-10-15T16:02:08Z","snapshot_observed_at":"2026-07-06T19:33:57.090585Z","submitted_at":"2024-10-15T16:02:08Z","title":"Patch-Based Diffusion Models Beat Whole-Image Models for Mismatched Distribution Inverse Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.11730","snapshot_observed_at":"2026-08-07T11:01:11.648102Z","title":"Patch-based diffusion models beat whole-image models for mismatched distribution inverse problems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:11.648102Z"},"links":{"cited_paper":"/paper/2410.11730","citing_paper":"/paper/2506.03804"},"observation_digest":"sha256:6e59147e421bd660329f67b22c4bc884960e649f9d43940763515aa6be491ed6","observation_id":"578b3786-07e7-4218-9e70-e99c4c9599b3","resolution":{"observed_at":"2026-08-07T11:01:11.648102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.03804","last_updated":"2025-08-27T10:57:02Z","latest_version":2,"primary_category":"physics.med-ph","snapshot_observed_at":"2026-08-07T10:52:39.160124Z","submitted_at":"2025-06-04T10:24:14Z","title":"Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":1,"metadata_mismatch":12,"parse_uncertain":0,"unresolved":15,"verified_exact":11,"verified_fuzzy":1},"total_outbound_references":40},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.03804."}