{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:DGLY7QMV76QAOTPIPRK4GJPZ7S","short_pith_number":"pith:DGLY7QMV","canonical_record":{"source":{"id":"2207.11396","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-23T02:37:37Z","cross_cats_sorted":[],"title_canon_sha256":"b12b473defde7a6d76072681995fdf5083950207d44dec0d866a222d7a40ad0f","abstract_canon_sha256":"104b83ba14612b821c933d07c92e6e8bfcf2c3f1a03a56ae12b87e534e74e1a7"},"schema_version":"1.0"},"canonical_sha256":"19978fc195ffa0074de87c55c325f9fc83b85eb9407bd5b62ce30706305d0747","source":{"kind":"arxiv","id":"2207.11396","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.11396","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"arxiv_version","alias_value":"2207.11396v1","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.11396","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_12","alias_value":"DGLY7QMV76QA","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_16","alias_value":"DGLY7QMV76QAOTPI","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_8","alias_value":"DGLY7QMV","created_at":"2026-07-05T04:43:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:DGLY7QMV76QAOTPIPRK4GJPZ7S","target":"record","payload":{"canonical_record":{"source":{"id":"2207.11396","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-23T02:37:37Z","cross_cats_sorted":[],"title_canon_sha256":"b12b473defde7a6d76072681995fdf5083950207d44dec0d866a222d7a40ad0f","abstract_canon_sha256":"104b83ba14612b821c933d07c92e6e8bfcf2c3f1a03a56ae12b87e534e74e1a7"},"schema_version":"1.0"},"canonical_sha256":"19978fc195ffa0074de87c55c325f9fc83b85eb9407bd5b62ce30706305d0747","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:43:04.686413Z","signature_b64":"wPW6VVwMAlioI1BAYxOmdHHIArzdVERSNstLeDBB1Cd1eVi8YYCOOv4nd87jqs+NPFhCVLLJUOUOOBsbEeIHDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"19978fc195ffa0074de87c55c325f9fc83b85eb9407bd5b62ce30706305d0747","last_reissued_at":"2026-07-05T04:43:04.686012Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:43:04.686012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.11396","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:43:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bxRX8wL2ih4ungI5WmMOFAmL8/njgKlvNLLHcBbU25Qr3ORcLXgspgpaWF9Yf9zhbZAuGQi8gt8KB44n0HIyBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:19:00.216602Z"},"content_sha256":"d20a9028b89418c81232d2ae107b4cb7a4c6da7ac1091f476995ff0c364e03c6","schema_version":"1.0","event_id":"sha256:d20a9028b89418c81232d2ae107b4cb7a4c6da7ac1091f476995ff0c364e03c6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:DGLY7QMV76QAOTPIPRK4GJPZ7S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Orientation and Context Entangled Network for Retinal Vessel Segmentation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Danilo Bzdok, Kaifu Yang, Xinxu Wei, Yongjie Li","submitted_at":"2022-07-23T02:37:37Z","abstract_excerpt":"Most of the existing deep learning based methods for vessel segmentation neglect two important aspects of retinal vessels, one is the orientation information of vessels, and the other is the contextual information of the whole fundus region. In this paper, we propose a robust Orientation and Context Entangled Network (denoted as OCE-Net), which has the capability of extracting complex orientation and context information of the blood vessels. To achieve complex orientation aware, a Dynamic Complex Orientation Aware Convolution (DCOA Conv) is proposed to extract complex vessels with multiple ori"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.11396","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/2207.11396/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":"2026-07-05T04:43:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eGf6A1zSxZGqesiQXj/X8yAjFBNnr0pJkZ0tD150pSZ0b7GsOnTjEbjIXnZfugdhwOR5qvdkEQZ7mN1ZnckHBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:19:00.216980Z"},"content_sha256":"a4ac7d2d6c5ae0e90beeb79921b5935475fa7a3a47f7367b06b800e75cf22b7a","schema_version":"1.0","event_id":"sha256:a4ac7d2d6c5ae0e90beeb79921b5935475fa7a3a47f7367b06b800e75cf22b7a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/bundle.json","state_url":"https://pith.science/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/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":"2026-07-07T06:19:00Z","links":{"resolver":"https://pith.science/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S","bundle":"https://pith.science/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/bundle.json","state":"https://pith.science/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DGLY7QMV76QAOTPIPRK4GJPZ7S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DGLY7QMV76QAOTPIPRK4GJPZ7S","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":"104b83ba14612b821c933d07c92e6e8bfcf2c3f1a03a56ae12b87e534e74e1a7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-23T02:37:37Z","title_canon_sha256":"b12b473defde7a6d76072681995fdf5083950207d44dec0d866a222d7a40ad0f"},"schema_version":"1.0","source":{"id":"2207.11396","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.11396","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"arxiv_version","alias_value":"2207.11396v1","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.11396","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_12","alias_value":"DGLY7QMV76QA","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_16","alias_value":"DGLY7QMV76QAOTPI","created_at":"2026-07-05T04:43:04Z"},{"alias_kind":"pith_short_8","alias_value":"DGLY7QMV","created_at":"2026-07-05T04:43:04Z"}],"graph_snapshots":[{"event_id":"sha256:a4ac7d2d6c5ae0e90beeb79921b5935475fa7a3a47f7367b06b800e75cf22b7a","target":"graph","created_at":"2026-07-05T04:43:04Z","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/2207.11396/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most of the existing deep learning based methods for vessel segmentation neglect two important aspects of retinal vessels, one is the orientation information of vessels, and the other is the contextual information of the whole fundus region. In this paper, we propose a robust Orientation and Context Entangled Network (denoted as OCE-Net), which has the capability of extracting complex orientation and context information of the blood vessels. To achieve complex orientation aware, a Dynamic Complex Orientation Aware Convolution (DCOA Conv) is proposed to extract complex vessels with multiple ori","authors_text":"Danilo Bzdok, Kaifu Yang, Xinxu Wei, Yongjie Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-23T02:37:37Z","title":"Orientation and Context Entangled Network for Retinal Vessel Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.11396","kind":"arxiv","version":1},"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:d20a9028b89418c81232d2ae107b4cb7a4c6da7ac1091f476995ff0c364e03c6","target":"record","created_at":"2026-07-05T04:43:04Z","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":"104b83ba14612b821c933d07c92e6e8bfcf2c3f1a03a56ae12b87e534e74e1a7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-23T02:37:37Z","title_canon_sha256":"b12b473defde7a6d76072681995fdf5083950207d44dec0d866a222d7a40ad0f"},"schema_version":"1.0","source":{"id":"2207.11396","kind":"arxiv","version":1}},"canonical_sha256":"19978fc195ffa0074de87c55c325f9fc83b85eb9407bd5b62ce30706305d0747","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"19978fc195ffa0074de87c55c325f9fc83b85eb9407bd5b62ce30706305d0747","first_computed_at":"2026-07-05T04:43:04.686012Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:43:04.686012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wPW6VVwMAlioI1BAYxOmdHHIArzdVERSNstLeDBB1Cd1eVi8YYCOOv4nd87jqs+NPFhCVLLJUOUOOBsbEeIHDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:43:04.686413Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.11396","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d20a9028b89418c81232d2ae107b4cb7a4c6da7ac1091f476995ff0c364e03c6","sha256:a4ac7d2d6c5ae0e90beeb79921b5935475fa7a3a47f7367b06b800e75cf22b7a"],"state_sha256":"cce5d808a7e581c00bee51c3611e34dff7548cfd9b2e94d7e7b075a4d328b6e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nBEAjsUN++xcHkpXCJz9hYXJuI1fVkcJUoi11VcLVAI+m+ogxFD+3LEkgH1f/10NarxfwYFaYbQf0Ho9ZUR6Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T06:19:00.219200Z","bundle_sha256":"303de815f241c0dce2fad877b242ba347bbfafaef0d02e19acddb8ff283cc9be"}}