{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:6AXHY755BWKO2DTQYUGFJOZIPS","short_pith_number":"pith:6AXHY755","canonical_record":{"source":{"id":"2203.04294","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T04:23:47Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"e0214f8c196e70eea1c1cc19a8b6a351c636c9c37d676d0a2c2fb1d6301b6ebf","abstract_canon_sha256":"a3324f470ca9217d7159f76b536f3f2e6e9318a15ab1d1be00608e7e741edb40"},"schema_version":"1.0"},"canonical_sha256":"f02e7c7fbd0d94ed0e70c50c54bb287c955ba87a7a2beb125378e62036a51bfd","source":{"kind":"arxiv","id":"2203.04294","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04294","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04294v3","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04294","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_12","alias_value":"6AXHY755BWKO","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_16","alias_value":"6AXHY755BWKO2DTQ","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_8","alias_value":"6AXHY755","created_at":"2026-07-05T06:21:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:6AXHY755BWKO2DTQYUGFJOZIPS","target":"record","payload":{"canonical_record":{"source":{"id":"2203.04294","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T04:23:47Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"e0214f8c196e70eea1c1cc19a8b6a351c636c9c37d676d0a2c2fb1d6301b6ebf","abstract_canon_sha256":"a3324f470ca9217d7159f76b536f3f2e6e9318a15ab1d1be00608e7e741edb40"},"schema_version":"1.0"},"canonical_sha256":"f02e7c7fbd0d94ed0e70c50c54bb287c955ba87a7a2beb125378e62036a51bfd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:21:27.171855Z","signature_b64":"sjSxLWpF2LKOXO7pnB+o3UwyC+EAA8Ob9+7LdoEoZd+E3dywTiAFTlDcx/P3sBrhF9d85i6V7BkitMC3DDg9CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f02e7c7fbd0d94ed0e70c50c54bb287c955ba87a7a2beb125378e62036a51bfd","last_reissued_at":"2026-07-05T06:21:27.171398Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:21:27.171398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.04294","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:21:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mofRs9d7uD/FtLNHE9Z9ndMzITmTFyuMMV61QK49WCJ7zGz21AVsWwM2lwxNOl25jZ2w9ZzGkMQODRjtd7xPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:43:37.248148Z"},"content_sha256":"38d2ad13398e0c0e9412f72f528b29774951b5014b4c059732edc186a7dccc6a","schema_version":"1.0","event_id":"sha256:38d2ad13398e0c0e9412f72f528b29774951b5014b4c059732edc186a7dccc6a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:6AXHY755BWKO2DTQYUGFJOZIPS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipeline","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"eess.IV","authors_text":"Andong Wang, Ho Ming Poon, Kun-Chang Yu, Terence Chi Chun Tam, Wei-Ning Lee","submitted_at":"2022-03-08T04:23:47Z","abstract_excerpt":"Airway segmentation is essential for chest CT image analysis. Different from natural image segmentation, which pursues high pixel-wise accuracy, airway segmentation focuses on topology. The task is challenging not only because of its complex tree-like structure but also the severe pixel imbalance among airway branches of different generations. To tackle the problems, we present a NaviAirway method which consists of a bronchiole-sensitive loss function for airway topology preservation and an iterative training strategy for accurate model learning across different airway generations. To suppleme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04294","kind":"arxiv","version":3},"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/2203.04294/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":"2026-07-05T06:21:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q8Tf9yPbfiTkVAONRkI32+3naSlRUu+ctICPDmDhmeF8MH7ZU+KWbSoZIFmlEucmW+pyUl74uSofYwiYv0H1DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:43:37.248726Z"},"content_sha256":"3aa41ef24d297062577deef1c1875110e43af0589fed7a0f34dd741bbddf17aa","schema_version":"1.0","event_id":"sha256:3aa41ef24d297062577deef1c1875110e43af0589fed7a0f34dd741bbddf17aa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6AXHY755BWKO2DTQYUGFJOZIPS/bundle.json","state_url":"https://pith.science/pith/6AXHY755BWKO2DTQYUGFJOZIPS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6AXHY755BWKO2DTQYUGFJOZIPS/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":"2026-08-07T16:43:37Z","links":{"resolver":"https://pith.science/pith/6AXHY755BWKO2DTQYUGFJOZIPS","bundle":"https://pith.science/pith/6AXHY755BWKO2DTQYUGFJOZIPS/bundle.json","state":"https://pith.science/pith/6AXHY755BWKO2DTQYUGFJOZIPS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6AXHY755BWKO2DTQYUGFJOZIPS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6AXHY755BWKO2DTQYUGFJOZIPS","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":"a3324f470ca9217d7159f76b536f3f2e6e9318a15ab1d1be00608e7e741edb40","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T04:23:47Z","title_canon_sha256":"e0214f8c196e70eea1c1cc19a8b6a351c636c9c37d676d0a2c2fb1d6301b6ebf"},"schema_version":"1.0","source":{"id":"2203.04294","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04294","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04294v3","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04294","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_12","alias_value":"6AXHY755BWKO","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_16","alias_value":"6AXHY755BWKO2DTQ","created_at":"2026-07-05T06:21:27Z"},{"alias_kind":"pith_short_8","alias_value":"6AXHY755","created_at":"2026-07-05T06:21:27Z"}],"graph_snapshots":[{"event_id":"sha256:3aa41ef24d297062577deef1c1875110e43af0589fed7a0f34dd741bbddf17aa","target":"graph","created_at":"2026-07-05T06:21:27Z","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/2203.04294/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Airway segmentation is essential for chest CT image analysis. Different from natural image segmentation, which pursues high pixel-wise accuracy, airway segmentation focuses on topology. The task is challenging not only because of its complex tree-like structure but also the severe pixel imbalance among airway branches of different generations. To tackle the problems, we present a NaviAirway method which consists of a bronchiole-sensitive loss function for airway topology preservation and an iterative training strategy for accurate model learning across different airway generations. To suppleme","authors_text":"Andong Wang, Ho Ming Poon, Kun-Chang Yu, Terence Chi Chun Tam, Wei-Ning Lee","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T04:23:47Z","title":"NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipeline"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04294","kind":"arxiv","version":3},"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":"sha256:38d2ad13398e0c0e9412f72f528b29774951b5014b4c059732edc186a7dccc6a","target":"record","created_at":"2026-07-05T06:21:27Z","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":"a3324f470ca9217d7159f76b536f3f2e6e9318a15ab1d1be00608e7e741edb40","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T04:23:47Z","title_canon_sha256":"e0214f8c196e70eea1c1cc19a8b6a351c636c9c37d676d0a2c2fb1d6301b6ebf"},"schema_version":"1.0","source":{"id":"2203.04294","kind":"arxiv","version":3}},"canonical_sha256":"f02e7c7fbd0d94ed0e70c50c54bb287c955ba87a7a2beb125378e62036a51bfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f02e7c7fbd0d94ed0e70c50c54bb287c955ba87a7a2beb125378e62036a51bfd","first_computed_at":"2026-07-05T06:21:27.171398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:21:27.171398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sjSxLWpF2LKOXO7pnB+o3UwyC+EAA8Ob9+7LdoEoZd+E3dywTiAFTlDcx/P3sBrhF9d85i6V7BkitMC3DDg9CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:21:27.171855Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.04294","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:38d2ad13398e0c0e9412f72f528b29774951b5014b4c059732edc186a7dccc6a","sha256:3aa41ef24d297062577deef1c1875110e43af0589fed7a0f34dd741bbddf17aa"],"state_sha256":"6bf60b1809de37ee7fbb9a6833d533da33080b7cd93c8dc5c0308c7299ea775a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oNHRUDjiITMPK13IiHMOBV/TQ7I0LjB7qUfJfPrGPPPS0Syw2wck6SOX4CldWSDEvVOVs579nwMv7LIjcA1vBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T16:43:37.254336Z","bundle_sha256":"9e9e0f4b4e6ad3909f27bdb5f52ae3db8543c6a985d690b05c1e4b8d7c76ace5"}}