{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WZBU3BHFCYCAXROXMU3DWKRJ2B","short_pith_number":"pith:WZBU3BHF","canonical_record":{"source":{"id":"2506.12395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-14T08:20:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"04b3a677e0f7b359e48b8a6914af5b4b1b8451b820ebbe4c1d095468b9421bd4","abstract_canon_sha256":"749c928d7db495773f9be85d0ef3e7ff54239a2c0f467cb69b2b3cb338f24d2a"},"schema_version":"1.0"},"canonical_sha256":"b6434d84e516040bc5d765363b2a29d05bf7780a2b39d1a6a0b673eb53e7e248","source":{"kind":"arxiv","id":"2506.12395","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.12395","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"arxiv_version","alias_value":"2506.12395v1","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.12395","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_12","alias_value":"WZBU3BHFCYCA","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_16","alias_value":"WZBU3BHFCYCAXROX","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_8","alias_value":"WZBU3BHF","created_at":"2026-07-05T11:22:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WZBU3BHFCYCAXROXMU3DWKRJ2B","target":"record","payload":{"canonical_record":{"source":{"id":"2506.12395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-14T08:20:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"04b3a677e0f7b359e48b8a6914af5b4b1b8451b820ebbe4c1d095468b9421bd4","abstract_canon_sha256":"749c928d7db495773f9be85d0ef3e7ff54239a2c0f467cb69b2b3cb338f24d2a"},"schema_version":"1.0"},"canonical_sha256":"b6434d84e516040bc5d765363b2a29d05bf7780a2b39d1a6a0b673eb53e7e248","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:19.240893Z","signature_b64":"IuvqTRGS01uhw/knAnIfYSh7hJ+bVcU997lEMLpp7uEvQuIZpWqnSeQHHCpSZssUunjoxVEDpq7Q7PtWcVdwDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6434d84e516040bc5d765363b2a29d05bf7780a2b39d1a6a0b673eb53e7e248","last_reissued_at":"2026-07-05T11:22:19.240320Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:19.240320Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.12395","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":"2026-07-05T11:22:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3ORC8rLTV0AEWS0clcvef3hI4HfdeMcCMliVQag5QBaIodidFwes9imTmhWXwLS2ixEq81mzweICcoujbDi5Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:07:21.573085Z"},"content_sha256":"08eedfa17f992bfa955163824d09978fc35f551a6fad830d0f32cb55b70eb5b2","schema_version":"1.0","event_id":"sha256:08eedfa17f992bfa955163824d09978fc35f551a6fad830d0f32cb55b70eb5b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WZBU3BHFCYCAXROXMU3DWKRJ2B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Shape-aware Sampling Matters in the Modeling of Multi-Class Tubular Structures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Hanxiao Zhang, Minghui Zhang, Xin You, Yaoyu Liu, Yun Gu","submitted_at":"2025-06-14T08:20:08Z","abstract_excerpt":"Accurate multi-class tubular modeling is critical for precise lesion localization and optimal treatment planning. Deep learning methods enable automated shape modeling by prioritizing volumetric overlap accuracy. However, the inherent complexity of fine-grained semantic tubular shapes is not fully emphasized by overlap accuracy, resulting in reduced topological preservation. To address this, we propose the Shapeaware Sampling (SAS), which optimizes patchsize allocation for online sampling and extracts a topology-preserved skeletal representation for the objective function. Fractal Dimension-ba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.12395","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/2506.12395/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":"2026-07-05T11:22:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DJB5cJrrDFpErbtq3gO11EeMHT/Mdt6xesLAO/MCo7eCVh7AFJXBj883HeKYZE1kfRxsWZVsnCVyOxQ6n7f/CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:07:21.573970Z"},"content_sha256":"dd7d47fa30c2d826c70ec5f8872e1eb62f30525931323dd26042781cb64fc58b","schema_version":"1.0","event_id":"sha256:dd7d47fa30c2d826c70ec5f8872e1eb62f30525931323dd26042781cb64fc58b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/bundle.json","state_url":"https://pith.science/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/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":"2026-08-09T13:07:21Z","links":{"resolver":"https://pith.science/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B","bundle":"https://pith.science/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/bundle.json","state":"https://pith.science/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WZBU3BHFCYCAXROXMU3DWKRJ2B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WZBU3BHFCYCAXROXMU3DWKRJ2B","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":"749c928d7db495773f9be85d0ef3e7ff54239a2c0f467cb69b2b3cb338f24d2a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-14T08:20:08Z","title_canon_sha256":"04b3a677e0f7b359e48b8a6914af5b4b1b8451b820ebbe4c1d095468b9421bd4"},"schema_version":"1.0","source":{"id":"2506.12395","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.12395","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"arxiv_version","alias_value":"2506.12395v1","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.12395","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_12","alias_value":"WZBU3BHFCYCA","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_16","alias_value":"WZBU3BHFCYCAXROX","created_at":"2026-07-05T11:22:19Z"},{"alias_kind":"pith_short_8","alias_value":"WZBU3BHF","created_at":"2026-07-05T11:22:19Z"}],"graph_snapshots":[{"event_id":"sha256:dd7d47fa30c2d826c70ec5f8872e1eb62f30525931323dd26042781cb64fc58b","target":"graph","created_at":"2026-07-05T11:22:19Z","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/2506.12395/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate multi-class tubular modeling is critical for precise lesion localization and optimal treatment planning. Deep learning methods enable automated shape modeling by prioritizing volumetric overlap accuracy. However, the inherent complexity of fine-grained semantic tubular shapes is not fully emphasized by overlap accuracy, resulting in reduced topological preservation. To address this, we propose the Shapeaware Sampling (SAS), which optimizes patchsize allocation for online sampling and extracts a topology-preserved skeletal representation for the objective function. Fractal Dimension-ba","authors_text":"Hanxiao Zhang, Minghui Zhang, Xin You, Yaoyu Liu, Yun Gu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-14T08:20:08Z","title":"Shape-aware Sampling Matters in the Modeling of Multi-Class Tubular Structures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.12395","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":"sha256:08eedfa17f992bfa955163824d09978fc35f551a6fad830d0f32cb55b70eb5b2","target":"record","created_at":"2026-07-05T11:22:19Z","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":"749c928d7db495773f9be85d0ef3e7ff54239a2c0f467cb69b2b3cb338f24d2a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-14T08:20:08Z","title_canon_sha256":"04b3a677e0f7b359e48b8a6914af5b4b1b8451b820ebbe4c1d095468b9421bd4"},"schema_version":"1.0","source":{"id":"2506.12395","kind":"arxiv","version":1}},"canonical_sha256":"b6434d84e516040bc5d765363b2a29d05bf7780a2b39d1a6a0b673eb53e7e248","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6434d84e516040bc5d765363b2a29d05bf7780a2b39d1a6a0b673eb53e7e248","first_computed_at":"2026-07-05T11:22:19.240320Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:19.240320Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IuvqTRGS01uhw/knAnIfYSh7hJ+bVcU997lEMLpp7uEvQuIZpWqnSeQHHCpSZssUunjoxVEDpq7Q7PtWcVdwDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:19.240893Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.12395","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08eedfa17f992bfa955163824d09978fc35f551a6fad830d0f32cb55b70eb5b2","sha256:dd7d47fa30c2d826c70ec5f8872e1eb62f30525931323dd26042781cb64fc58b"],"state_sha256":"0145aacbbf63d8a3d609c31d8da7485833f238e186dd7385c9fac7cc9355e7b9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eik/jikf+dseFkpZElf8aDbf1UOiwxLz5MSf10BdVdNIH5zLZ7NdqgvuI6RpN2QPon9NWV4PXPKPWE7fGkUUBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:07:21.579414Z","bundle_sha256":"f97711f57ab94a118d542bfeab191c7d0cbb81b549308330f21b93b1fb029a58"}}