{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:G2Y5ARLYCW5UYKRWDIMBNJYBC3","short_pith_number":"pith:G2Y5ARLY","canonical_record":{"source":{"id":"2506.00727","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T22:02:05Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"d5c02dd5ac2d1a823acb400e38f34845f5c9948ebb14ee78abb9d146761005eb","abstract_canon_sha256":"9b95b2401230460c0bbaa2042bf023b4b402cbbf32dbea3fdffaeb1cb845accf"},"schema_version":"1.0"},"canonical_sha256":"36b1d0457815bb4c2a361a1816a70116dea189912b43ed097ea222c8f080f31c","source":{"kind":"arxiv","id":"2506.00727","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00727","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00727v2","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00727","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_12","alias_value":"G2Y5ARLYCW5U","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_16","alias_value":"G2Y5ARLYCW5UYKRW","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_8","alias_value":"G2Y5ARLY","created_at":"2026-08-04T02:08:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:G2Y5ARLYCW5UYKRWDIMBNJYBC3","target":"record","payload":{"canonical_record":{"source":{"id":"2506.00727","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T22:02:05Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"d5c02dd5ac2d1a823acb400e38f34845f5c9948ebb14ee78abb9d146761005eb","abstract_canon_sha256":"9b95b2401230460c0bbaa2042bf023b4b402cbbf32dbea3fdffaeb1cb845accf"},"schema_version":"1.0"},"canonical_sha256":"36b1d0457815bb4c2a361a1816a70116dea189912b43ed097ea222c8f080f31c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T02:08:06.540647Z","signature_b64":"K+vq00d0KZWaALr43HQOaPKa0y1ggmCl+u2jOWHwLnOTIEjf9ToUCtA5cj+A86U0eY7/f05OTZoRRldyt6I1Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36b1d0457815bb4c2a361a1816a70116dea189912b43ed097ea222c8f080f31c","last_reissued_at":"2026-08-04T02:08:06.538675Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T02:08:06.538675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.00727","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-04T02:08:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V2dRFzEt7+zeWjEtAUpQeZkpStbLsT91HCz/FTFOSUactbzuleFC8U/MRARL9nb0sHuL9IZVo2tc0Q0LG0zjCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T01:22:58.808876Z"},"content_sha256":"ea75ec85d2fcbb21d3bb69cc7bc9b14496889b83d22a6af37807bcb5805c7c96","schema_version":"1.0","event_id":"sha256:ea75ec85d2fcbb21d3bb69cc7bc9b14496889b83d22a6af37807bcb5805c7c96"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:G2Y5ARLYCW5UYKRWDIMBNJYBC3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Plane Reformatting for 4D Flow MRI using Deep Reinforcement Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Cristi\\'an Tejos, Francesca Raimondi, Javier Bisbal, Jos\\'e Rodriguez-Palomarez, Julio Garc\\'ia, Julio Sotelo, Marcelo E Andia, Maria I Vald\\'es, Pablo Irarrazaval, Sergio Uribe","submitted_at":"2025-05-31T22:02:05Z","abstract_excerpt":"Background and Objective: Plane reformatting for four-dimensional phase contrast MRI (4D flow MRI) is time-consuming and prone to inter-observer variability, which limits fast cardiovascular flow assessment. Deep reinforcement learning (DRL) trains agents to iteratively adjust plane position and orientation, enabling accurate plane reformatting without the need for detailed landmarks, making it suitable for images with limited contrast and resolution such as 4D flow MRI. However, current DRL methods assume that test volumes share the same spatial alignment as the training data, limiting genera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00727","kind":"arxiv","version":2},"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/2506.00727/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-04T02:08:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WZZKZ2LMIjGgKv0REdv4GPtteDXwfvm1zawyVOCPKUGfd3G8Cs8pHBbFpIhNB3Hf+6LuIdxK/yCzENSAOarxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T01:22:58.809508Z"},"content_sha256":"97b6570b85ac591320dcfcf13a02265bc85f2b1e5ce57e0f9b411b54b590e40b","schema_version":"1.0","event_id":"sha256:97b6570b85ac591320dcfcf13a02265bc85f2b1e5ce57e0f9b411b54b590e40b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/bundle.json","state_url":"https://pith.science/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T01:22:58Z","links":{"resolver":"https://pith.science/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3","bundle":"https://pith.science/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/bundle.json","state":"https://pith.science/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G2Y5ARLYCW5UYKRWDIMBNJYBC3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:G2Y5ARLYCW5UYKRWDIMBNJYBC3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9b95b2401230460c0bbaa2042bf023b4b402cbbf32dbea3fdffaeb1cb845accf","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T22:02:05Z","title_canon_sha256":"d5c02dd5ac2d1a823acb400e38f34845f5c9948ebb14ee78abb9d146761005eb"},"schema_version":"1.0","source":{"id":"2506.00727","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00727","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00727v2","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00727","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_12","alias_value":"G2Y5ARLYCW5U","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_16","alias_value":"G2Y5ARLYCW5UYKRW","created_at":"2026-08-04T02:08:06Z"},{"alias_kind":"pith_short_8","alias_value":"G2Y5ARLY","created_at":"2026-08-04T02:08:06Z"}],"graph_snapshots":[{"event_id":"sha256:97b6570b85ac591320dcfcf13a02265bc85f2b1e5ce57e0f9b411b54b590e40b","target":"graph","created_at":"2026-08-04T02:08:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2506.00727/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Background and Objective: Plane reformatting for four-dimensional phase contrast MRI (4D flow MRI) is time-consuming and prone to inter-observer variability, which limits fast cardiovascular flow assessment. Deep reinforcement learning (DRL) trains agents to iteratively adjust plane position and orientation, enabling accurate plane reformatting without the need for detailed landmarks, making it suitable for images with limited contrast and resolution such as 4D flow MRI. However, current DRL methods assume that test volumes share the same spatial alignment as the training data, limiting genera","authors_text":"Cristi\\'an Tejos, Francesca Raimondi, Javier Bisbal, Jos\\'e Rodriguez-Palomarez, Julio Garc\\'ia, Julio Sotelo, Marcelo E Andia, Maria I Vald\\'es, Pablo Irarrazaval, Sergio Uribe","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T22:02:05Z","title":"Adaptive Plane Reformatting for 4D Flow MRI using Deep Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00727","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ea75ec85d2fcbb21d3bb69cc7bc9b14496889b83d22a6af37807bcb5805c7c96","target":"record","created_at":"2026-08-04T02:08:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9b95b2401230460c0bbaa2042bf023b4b402cbbf32dbea3fdffaeb1cb845accf","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T22:02:05Z","title_canon_sha256":"d5c02dd5ac2d1a823acb400e38f34845f5c9948ebb14ee78abb9d146761005eb"},"schema_version":"1.0","source":{"id":"2506.00727","kind":"arxiv","version":2}},"canonical_sha256":"36b1d0457815bb4c2a361a1816a70116dea189912b43ed097ea222c8f080f31c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36b1d0457815bb4c2a361a1816a70116dea189912b43ed097ea222c8f080f31c","first_computed_at":"2026-08-04T02:08:06.538675Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:08:06.538675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K+vq00d0KZWaALr43HQOaPKa0y1ggmCl+u2jOWHwLnOTIEjf9ToUCtA5cj+A86U0eY7/f05OTZoRRldyt6I1Aw==","signature_status":"signed_v1","signed_at":"2026-08-04T02:08:06.540647Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.00727","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ea75ec85d2fcbb21d3bb69cc7bc9b14496889b83d22a6af37807bcb5805c7c96","sha256:97b6570b85ac591320dcfcf13a02265bc85f2b1e5ce57e0f9b411b54b590e40b"],"state_sha256":"93a11f2249109b81f811304f19ebc041b0daa8991e0b9abfd19247ebfb082818"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J9QdLtiBFzIT2LxKsKQEXNZKBu2z99R63G6p7t95VzfR+32KbdJltXW9PG+KtqzI0Xjkcvwt6Pp9GBfGSmw5Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T01:22:58.813906Z","bundle_sha256":"aa8aebe66c60c2e77fa107b36c51e85dbb78cbef227996f2ca334596e24d7834"}}