{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CVXKF6MCMNZWMLG2DAT2JM6OV3","short_pith_number":"pith:CVXKF6MC","canonical_record":{"source":{"id":"1805.08676","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-22T15:47:41Z","cross_cats_sorted":[],"title_canon_sha256":"a9a1a4df3d98aae53fb0da234061e379780b6f5dd0e3ae6671f5174ecbb36aac","abstract_canon_sha256":"0d618066bb7c14eae60e59e812f8985dd1f2745540fb019e4a9cb8ddade1b0d4"},"schema_version":"1.0"},"canonical_sha256":"156ea2f9826373662cda1827a4b3ceaecbfaa61358c16a1405dbce348f9b0cc9","source":{"kind":"arxiv","id":"1805.08676","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08676","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08676v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08676","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"CVXKF6MCMNZW","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"CVXKF6MCMNZWMLG2","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"CVXKF6MC","created_at":"2026-05-18T12:32:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CVXKF6MCMNZWMLG2DAT2JM6OV3","target":"record","payload":{"canonical_record":{"source":{"id":"1805.08676","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-22T15:47:41Z","cross_cats_sorted":[],"title_canon_sha256":"a9a1a4df3d98aae53fb0da234061e379780b6f5dd0e3ae6671f5174ecbb36aac","abstract_canon_sha256":"0d618066bb7c14eae60e59e812f8985dd1f2745540fb019e4a9cb8ddade1b0d4"},"schema_version":"1.0"},"canonical_sha256":"156ea2f9826373662cda1827a4b3ceaecbfaa61358c16a1405dbce348f9b0cc9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:25.457407Z","signature_b64":"ZyhYj+I6K73kVYpKmFxgyCC1ySSw9bjEoVd4Ku4bAAXYbCWNIw1fwHTGaA3n69z25o/phnn0l82IXL6IunvOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"156ea2f9826373662cda1827a4b3ceaecbfaa61358c16a1405dbce348f9b0cc9","last_reissued_at":"2026-05-18T00:15:25.456555Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:25.456555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.08676","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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"noVbHC7UUZ1cBxtjxNllxXzTaklBZrbvvOlpBce9AbXyiZkF32hQlBBsDx62Aztucg7TLMR/S77WPfL/9sklDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T06:59:37.684288Z"},"content_sha256":"eb02759cca1c0cd424b5b10d7dc3aa872b8bc6b80a80fa580e013c8d1f56b5ff","schema_version":"1.0","event_id":"sha256:eb02759cca1c0cd424b5b10d7dc3aa872b8bc6b80a80fa580e013c8d1f56b5ff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CVXKF6MCMNZWMLG2DAT2JM6OV3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Convexity Shape Prior for Level Set based Image Segmentation Method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hai-yang Huang, Jun Liu, Shi Yan, Xue-Cheng Tai","submitted_at":"2018-05-22T15:47:41Z","abstract_excerpt":"We propose a geometric convexity shape prior preservation method for variational level set based image segmentation methods. Our method is built upon the fact that the level set of a convex signed distanced function must be convex. This property enables us to transfer a complicated geometrical convexity prior into a simple inequality constraint on the function. An active set based Gauss-Seidel iteration is used to handle this constrained minimization problem to get an efficient algorithm. We apply our method to region and edge based level set segmentation models including Chan-Vese (CV) model "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08676","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":""},"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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LCIAqnmr0gDzytJFa6SQN3nONFeiqbN2jrjKCmwFtyWDGh6YarGCiPIxnFbxkJliwNaJk1y1m0L0slZvOj4dDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T06:59:37.684950Z"},"content_sha256":"076c23158f4a119a7946523985d9194b63c4e0cb1f78f232b8c08bba5688c00e","schema_version":"1.0","event_id":"sha256:076c23158f4a119a7946523985d9194b63c4e0cb1f78f232b8c08bba5688c00e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/bundle.json","state_url":"https://pith.science/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/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":"2026-05-27T06:59:37Z","links":{"resolver":"https://pith.science/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3","bundle":"https://pith.science/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/bundle.json","state":"https://pith.science/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CVXKF6MCMNZWMLG2DAT2JM6OV3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CVXKF6MCMNZWMLG2DAT2JM6OV3","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":"0d618066bb7c14eae60e59e812f8985dd1f2745540fb019e4a9cb8ddade1b0d4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-22T15:47:41Z","title_canon_sha256":"a9a1a4df3d98aae53fb0da234061e379780b6f5dd0e3ae6671f5174ecbb36aac"},"schema_version":"1.0","source":{"id":"1805.08676","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08676","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08676v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08676","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"CVXKF6MCMNZW","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"CVXKF6MCMNZWMLG2","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"CVXKF6MC","created_at":"2026-05-18T12:32:19Z"}],"graph_snapshots":[{"event_id":"sha256:076c23158f4a119a7946523985d9194b63c4e0cb1f78f232b8c08bba5688c00e","target":"graph","created_at":"2026-05-18T00:15:25Z","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"},"paper":{"abstract_excerpt":"We propose a geometric convexity shape prior preservation method for variational level set based image segmentation methods. Our method is built upon the fact that the level set of a convex signed distanced function must be convex. This property enables us to transfer a complicated geometrical convexity prior into a simple inequality constraint on the function. An active set based Gauss-Seidel iteration is used to handle this constrained minimization problem to get an efficient algorithm. We apply our method to region and edge based level set segmentation models including Chan-Vese (CV) model ","authors_text":"Hai-yang Huang, Jun Liu, Shi Yan, Xue-Cheng Tai","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-22T15:47:41Z","title":"Convexity Shape Prior for Level Set based Image Segmentation Method"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08676","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:eb02759cca1c0cd424b5b10d7dc3aa872b8bc6b80a80fa580e013c8d1f56b5ff","target":"record","created_at":"2026-05-18T00:15:25Z","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":"0d618066bb7c14eae60e59e812f8985dd1f2745540fb019e4a9cb8ddade1b0d4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-22T15:47:41Z","title_canon_sha256":"a9a1a4df3d98aae53fb0da234061e379780b6f5dd0e3ae6671f5174ecbb36aac"},"schema_version":"1.0","source":{"id":"1805.08676","kind":"arxiv","version":1}},"canonical_sha256":"156ea2f9826373662cda1827a4b3ceaecbfaa61358c16a1405dbce348f9b0cc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"156ea2f9826373662cda1827a4b3ceaecbfaa61358c16a1405dbce348f9b0cc9","first_computed_at":"2026-05-18T00:15:25.456555Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:25.456555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZyhYj+I6K73kVYpKmFxgyCC1ySSw9bjEoVd4Ku4bAAXYbCWNIw1fwHTGaA3n69z25o/phnn0l82IXL6IunvOAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:25.457407Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.08676","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb02759cca1c0cd424b5b10d7dc3aa872b8bc6b80a80fa580e013c8d1f56b5ff","sha256:076c23158f4a119a7946523985d9194b63c4e0cb1f78f232b8c08bba5688c00e"],"state_sha256":"e6648906dcbb78fe89842cff0b43ebd1f89538fea797df73a30f5eb53f359dd7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UYHLih3z+ddoUKPSUhUhS9xj1eKTu8UU9n8GeIeh+0+xk6xKiY2wYoEmSmLwz5+CLBofAuf9AZtk3BepwBuMDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T06:59:37.687877Z","bundle_sha256":"c1dd46870cb701b0dd96ff5a7e506e9b5c3fafb405d495b7e767fe5cccccfa48"}}