{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KSHNI2RV5Q32HC3OSSTZQGFAFU","short_pith_number":"pith:KSHNI2RV","canonical_record":{"source":{"id":"2406.00492","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-01T16:45:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"350de486fa9c31a9c3a75e0ff05f113dd08a3ee1e166cbefae580a52a3594d30","abstract_canon_sha256":"d67997686dff046770b87de3a35834186b1b5605a235e152413b718b287e98e9"},"schema_version":"1.0"},"canonical_sha256":"548ed46a35ec37a38b6e94a79818a02d29fc08f084656471457f5d0c7e07d031","source":{"kind":"arxiv","id":"2406.00492","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.00492","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"arxiv_version","alias_value":"2406.00492v2","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.00492","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_12","alias_value":"KSHNI2RV5Q32","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_16","alias_value":"KSHNI2RV5Q32HC3O","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_8","alias_value":"KSHNI2RV","created_at":"2026-07-05T10:37:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KSHNI2RV5Q32HC3OSSTZQGFAFU","target":"record","payload":{"canonical_record":{"source":{"id":"2406.00492","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-01T16:45:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"350de486fa9c31a9c3a75e0ff05f113dd08a3ee1e166cbefae580a52a3594d30","abstract_canon_sha256":"d67997686dff046770b87de3a35834186b1b5605a235e152413b718b287e98e9"},"schema_version":"1.0"},"canonical_sha256":"548ed46a35ec37a38b6e94a79818a02d29fc08f084656471457f5d0c7e07d031","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:37:26.818572Z","signature_b64":"kK99cNSSPRefFdkAoxK0m0TpDWlqz1BszJ/99UPcwt75w4hTnmSSSv/chG+nMA8Wi0O/kXyegPKIaMYrX7DvCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"548ed46a35ec37a38b6e94a79818a02d29fc08f084656471457f5d0c7e07d031","last_reissued_at":"2026-07-05T10:37:26.818108Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:37:26.818108Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.00492","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":"2026-07-05T10:37:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lgesT5uP2PY0n6arUaLNN9yFLGk63MFzu8ZsqoxcmM0jptwMn3+K5grLqeLjoqQWhXy3AaFi62E4nGGpIhg6AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:27:59.327635Z"},"content_sha256":"04dbe416bbc0f22035480790c5e846c4918093a5abb852077a55cdd5521937e1","schema_version":"1.0","event_id":"sha256:04dbe416bbc0f22035480790c5e846c4918093a5abb852077a55cdd5521937e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KSHNI2RV5Q32HC3OSSTZQGFAFU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Deep Learning Model for Coronary Artery Segmentation and Quantitative Stenosis Detection in Angiographic Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Baixiang Huang, Guangyu Wei, Songyan He, Xueying Zeng, Yu Luo, Yushuang Shao","submitted_at":"2024-06-01T16:45:33Z","abstract_excerpt":"Coronary artery disease (CAD) is a leading cause of cardiovascular-related mortality, and accurate stenosis detection is crucial for effective clinical decision-making. Coronary angiography remains the gold standard for diagnosing CAD, but manual analysis of angiograms is prone to errors and subjectivity. This study aims to develop a deep learning-based approach for the automatic segmentation of coronary arteries from angiographic images and the quantitative detection of stenosis, thereby improving the accuracy and efficiency of CAD diagnosis. We propose a novel deep learning-based method for "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.00492","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/2406.00492/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":"2026-07-05T10:37:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g8LFYVYSOV/cL2nyR10r+ZCI9cnKvy1j66hVXTD24AHznTE/x5wOYsyPGlMpIxWUrAqLVnq2Bb3Prt/o6u5IAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:27:59.328546Z"},"content_sha256":"dd76e8871bd3a125e401f235272ab5c2ee55947251769e471d269613e055a529","schema_version":"1.0","event_id":"sha256:dd76e8871bd3a125e401f235272ab5c2ee55947251769e471d269613e055a529"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/bundle.json","state_url":"https://pith.science/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/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":"2026-08-06T03:27:59Z","links":{"resolver":"https://pith.science/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU","bundle":"https://pith.science/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/bundle.json","state":"https://pith.science/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KSHNI2RV5Q32HC3OSSTZQGFAFU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KSHNI2RV5Q32HC3OSSTZQGFAFU","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":"d67997686dff046770b87de3a35834186b1b5605a235e152413b718b287e98e9","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-01T16:45:33Z","title_canon_sha256":"350de486fa9c31a9c3a75e0ff05f113dd08a3ee1e166cbefae580a52a3594d30"},"schema_version":"1.0","source":{"id":"2406.00492","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.00492","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"arxiv_version","alias_value":"2406.00492v2","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.00492","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_12","alias_value":"KSHNI2RV5Q32","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_16","alias_value":"KSHNI2RV5Q32HC3O","created_at":"2026-07-05T10:37:26Z"},{"alias_kind":"pith_short_8","alias_value":"KSHNI2RV","created_at":"2026-07-05T10:37:26Z"}],"graph_snapshots":[{"event_id":"sha256:dd76e8871bd3a125e401f235272ab5c2ee55947251769e471d269613e055a529","target":"graph","created_at":"2026-07-05T10:37:26Z","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/2406.00492/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Coronary artery disease (CAD) is a leading cause of cardiovascular-related mortality, and accurate stenosis detection is crucial for effective clinical decision-making. Coronary angiography remains the gold standard for diagnosing CAD, but manual analysis of angiograms is prone to errors and subjectivity. This study aims to develop a deep learning-based approach for the automatic segmentation of coronary arteries from angiographic images and the quantitative detection of stenosis, thereby improving the accuracy and efficiency of CAD diagnosis. We propose a novel deep learning-based method for ","authors_text":"Baixiang Huang, Guangyu Wei, Songyan He, Xueying Zeng, Yu Luo, Yushuang Shao","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-01T16:45:33Z","title":"A Deep Learning Model for Coronary Artery Segmentation and Quantitative Stenosis Detection in Angiographic Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.00492","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":"sha256:04dbe416bbc0f22035480790c5e846c4918093a5abb852077a55cdd5521937e1","target":"record","created_at":"2026-07-05T10:37:26Z","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":"d67997686dff046770b87de3a35834186b1b5605a235e152413b718b287e98e9","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-01T16:45:33Z","title_canon_sha256":"350de486fa9c31a9c3a75e0ff05f113dd08a3ee1e166cbefae580a52a3594d30"},"schema_version":"1.0","source":{"id":"2406.00492","kind":"arxiv","version":2}},"canonical_sha256":"548ed46a35ec37a38b6e94a79818a02d29fc08f084656471457f5d0c7e07d031","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"548ed46a35ec37a38b6e94a79818a02d29fc08f084656471457f5d0c7e07d031","first_computed_at":"2026-07-05T10:37:26.818108Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:37:26.818108Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kK99cNSSPRefFdkAoxK0m0TpDWlqz1BszJ/99UPcwt75w4hTnmSSSv/chG+nMA8Wi0O/kXyegPKIaMYrX7DvCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:37:26.818572Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.00492","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:04dbe416bbc0f22035480790c5e846c4918093a5abb852077a55cdd5521937e1","sha256:dd76e8871bd3a125e401f235272ab5c2ee55947251769e471d269613e055a529"],"state_sha256":"2549635ace39947cc15361d56719a151b623b62c7376be6c42ea52ecc245b6ad"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uoTLUlhUOs0cn5lzzrAo+SHLxNqxy3EXsv+xrJLI0pl0/f55dVPRQSTHwvlvvU7oPD169lBdMu/goJIjWkI+Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T03:27:59.335330Z","bundle_sha256":"5bb8858a028341ebaea75fc0ef5d6bc0d589f461d80adef108dcf01b8520f8e3"}}