{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:J3PGI4W5RFKND2O5Q7F7HFXEWZ","short_pith_number":"pith:J3PGI4W5","schema_version":"1.0","canonical_sha256":"4ede6472dd8954d1e9dd87cbf396e4b666094c18bcf896742a537d0bb536c979","source":{"kind":"arxiv","id":"2606.24567","version":1},"attestation_state":"computed","paper":{"title":"Multilevel Stochastic Plug-and-Play for Sparse-View CT Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.med-ph"],"primary_cat":"cs.CV","authors_text":"Alexandre Bousse, Antoine De Paepe, Dimitris Visvikis","submitted_at":"2026-06-23T13:34:30Z","abstract_excerpt":"Sparse-view computed tomography (SVCT) reduces radiation exposure and acquisition time, but the limited number of projection views makes the reconstruction problem severely ill-posed and leads to streak artifacts when analytical methods are used. Plug-and-Play (PnP) methods provide an effective way to combine data fidelity with learned image priors, while stochastic PnP methods further improve robustness by matching the denoiser input distribution through re-noising. However, these methods often require many iterations to converge, which limits their practical efficiency. In this work, we prop"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.24567","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-23T13:34:30Z","cross_cats_sorted":["physics.med-ph"],"title_canon_sha256":"632d9d231688f9a95a04bd2aff90f8db5ebf1e6e07edeacb4c60f41ca132d2b8","abstract_canon_sha256":"65a5ebe927b1922fb67e7d6defaf1eef1d19e8452f39a9360413686188a35b2a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-24T01:15:34.106003Z","signature_b64":"e6/smuwLUCamSOdilp9J5w53FzNZXS7DnNBzu0o615whgiPxsLVXyFeSCYRfsMy2Ka/c8buWY6i8p/bk9LYKBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ede6472dd8954d1e9dd87cbf396e4b666094c18bcf896742a537d0bb536c979","last_reissued_at":"2026-06-24T01:15:34.105594Z","signature_status":"signed_v1","first_computed_at":"2026-06-24T01:15:34.105594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multilevel Stochastic Plug-and-Play for Sparse-View CT Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.med-ph"],"primary_cat":"cs.CV","authors_text":"Alexandre Bousse, Antoine De Paepe, Dimitris Visvikis","submitted_at":"2026-06-23T13:34:30Z","abstract_excerpt":"Sparse-view computed tomography (SVCT) reduces radiation exposure and acquisition time, but the limited number of projection views makes the reconstruction problem severely ill-posed and leads to streak artifacts when analytical methods are used. Plug-and-Play (PnP) methods provide an effective way to combine data fidelity with learned image priors, while stochastic PnP methods further improve robustness by matching the denoiser input distribution through re-noising. However, these methods often require many iterations to converge, which limits their practical efficiency. In this work, we prop"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24567","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.24567/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.24567","created_at":"2026-06-24T01:15:34.105661+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.24567v1","created_at":"2026-06-24T01:15:34.105661+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24567","created_at":"2026-06-24T01:15:34.105661+00:00"},{"alias_kind":"pith_short_12","alias_value":"J3PGI4W5RFKN","created_at":"2026-06-24T01:15:34.105661+00:00"},{"alias_kind":"pith_short_16","alias_value":"J3PGI4W5RFKND2O5","created_at":"2026-06-24T01:15:34.105661+00:00"},{"alias_kind":"pith_short_8","alias_value":"J3PGI4W5","created_at":"2026-06-24T01:15:34.105661+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ","json":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ.json","graph_json":"https://pith.science/api/pith-number/J3PGI4W5RFKND2O5Q7F7HFXEWZ/graph.json","events_json":"https://pith.science/api/pith-number/J3PGI4W5RFKND2O5Q7F7HFXEWZ/events.json","paper":"https://pith.science/paper/J3PGI4W5"},"agent_actions":{"view_html":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ","download_json":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ.json","view_paper":"https://pith.science/paper/J3PGI4W5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.24567&json=true","fetch_graph":"https://pith.science/api/pith-number/J3PGI4W5RFKND2O5Q7F7HFXEWZ/graph.json","fetch_events":"https://pith.science/api/pith-number/J3PGI4W5RFKND2O5Q7F7HFXEWZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ/action/storage_attestation","attest_author":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ/action/author_attestation","sign_citation":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ/action/citation_signature","submit_replication":"https://pith.science/pith/J3PGI4W5RFKND2O5Q7F7HFXEWZ/action/replication_record"}},"created_at":"2026-06-24T01:15:34.105661+00:00","updated_at":"2026-06-24T01:15:34.105661+00:00"}