{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:EJQDGA65TY6JFR7DPCR4VSZJTJ","short_pith_number":"pith:EJQDGA65","canonical_record":{"source":{"id":"1607.01092","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-05T02:19:57Z","cross_cats_sorted":[],"title_canon_sha256":"561a8ccb4e4160d000ce28098d2b91d5a1b9d7483a7e58c21ee5be9d0861f65d","abstract_canon_sha256":"10bf3dc6c2e807202603361b4105a50098c69c573be547ebfbb808409c78d485"},"schema_version":"1.0"},"canonical_sha256":"22603303dd9e3c92c7e378a3cacb299a71a59d6f040ff07437a51d9e770162d9","source":{"kind":"arxiv","id":"1607.01092","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.01092","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"arxiv_version","alias_value":"1607.01092v1","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.01092","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"pith_short_12","alias_value":"EJQDGA65TY6J","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EJQDGA65TY6JFR7D","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EJQDGA65","created_at":"2026-05-18T12:30:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:EJQDGA65TY6JFR7DPCR4VSZJTJ","target":"record","payload":{"canonical_record":{"source":{"id":"1607.01092","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-05T02:19:57Z","cross_cats_sorted":[],"title_canon_sha256":"561a8ccb4e4160d000ce28098d2b91d5a1b9d7483a7e58c21ee5be9d0861f65d","abstract_canon_sha256":"10bf3dc6c2e807202603361b4105a50098c69c573be547ebfbb808409c78d485"},"schema_version":"1.0"},"canonical_sha256":"22603303dd9e3c92c7e378a3cacb299a71a59d6f040ff07437a51d9e770162d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:30.170709Z","signature_b64":"YBujEuiH/8yFWP+ESxDLAhQqAa0fVRTuo9zf0GzLE6XvzY1sMJYbWBvp3G/40zOLd+qjW7saRbVBv92AF6srDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22603303dd9e3c92c7e378a3cacb299a71a59d6f040ff07437a51d9e770162d9","last_reissued_at":"2026-05-18T01:11:30.170370Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:30.170370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.01092","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":"2026-05-18T01:11:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SSpv5rrMOidiETozHjhIFZ0+O5EWw0YjQQ5KlFEpe+HHgmstbLmFi6jTOiSgr0PLwnde2GOZSh2Kr8mShLyiDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T19:38:14.773981Z"},"content_sha256":"0fdf4c9f52ffb0f529dc09279e84a6c1f340a6df51ad5ca5d27cbcd6c0236849","schema_version":"1.0","event_id":"sha256:0fdf4c9f52ffb0f529dc09279e84a6c1f340a6df51ad5ca5d27cbcd6c0236849"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:EJQDGA65TY6JFR7DPCR4VSZJTJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Incorporating prior knowledge in medical image segmentation: a survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ghassan Hamarneh, Masoud S. Nosrati","submitted_at":"2016-07-05T02:19:57Z","abstract_excerpt":"Medical image segmentation, the task of partitioning an image into meaningful parts, is an important step toward automating medical image analysis and is at the crux of a variety of medical imaging applications, such as computer aided diagnosis, therapy planning and delivery, and computer aided interventions. However, the existence of noise, low contrast and objects' complexity in medical images are critical obstacles that stand in the way of achieving an ideal segmentation system. Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.01092","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":"2026-05-18T01:11:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qL6zkm3uquOGXJhcKrqyrJG/ABmcGSh2X/1YYDdvimGjR/fuVxqV3Jc6zELyVquzfyrYMwF3eglGgJ8CflAoAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T19:38:14.774618Z"},"content_sha256":"efeeadd1bcd2885e19b0e76120513c3b405f2b5007f0416da2d013c816990a3a","schema_version":"1.0","event_id":"sha256:efeeadd1bcd2885e19b0e76120513c3b405f2b5007f0416da2d013c816990a3a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/bundle.json","state_url":"https://pith.science/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/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":"2026-06-04T19:38:14Z","links":{"resolver":"https://pith.science/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ","bundle":"https://pith.science/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/bundle.json","state":"https://pith.science/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EJQDGA65TY6JFR7DPCR4VSZJTJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:EJQDGA65TY6JFR7DPCR4VSZJTJ","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":"10bf3dc6c2e807202603361b4105a50098c69c573be547ebfbb808409c78d485","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-05T02:19:57Z","title_canon_sha256":"561a8ccb4e4160d000ce28098d2b91d5a1b9d7483a7e58c21ee5be9d0861f65d"},"schema_version":"1.0","source":{"id":"1607.01092","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.01092","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"arxiv_version","alias_value":"1607.01092v1","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.01092","created_at":"2026-05-18T01:11:30Z"},{"alias_kind":"pith_short_12","alias_value":"EJQDGA65TY6J","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EJQDGA65TY6JFR7D","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EJQDGA65","created_at":"2026-05-18T12:30:12Z"}],"graph_snapshots":[{"event_id":"sha256:efeeadd1bcd2885e19b0e76120513c3b405f2b5007f0416da2d013c816990a3a","target":"graph","created_at":"2026-05-18T01:11:30Z","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":"Medical image segmentation, the task of partitioning an image into meaningful parts, is an important step toward automating medical image analysis and is at the crux of a variety of medical imaging applications, such as computer aided diagnosis, therapy planning and delivery, and computer aided interventions. However, the existence of noise, low contrast and objects' complexity in medical images are critical obstacles that stand in the way of achieving an ideal segmentation system. Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate an","authors_text":"Ghassan Hamarneh, Masoud S. Nosrati","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-05T02:19:57Z","title":"Incorporating prior knowledge in medical image segmentation: a survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.01092","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":"sha256:0fdf4c9f52ffb0f529dc09279e84a6c1f340a6df51ad5ca5d27cbcd6c0236849","target":"record","created_at":"2026-05-18T01:11:30Z","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":"10bf3dc6c2e807202603361b4105a50098c69c573be547ebfbb808409c78d485","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-05T02:19:57Z","title_canon_sha256":"561a8ccb4e4160d000ce28098d2b91d5a1b9d7483a7e58c21ee5be9d0861f65d"},"schema_version":"1.0","source":{"id":"1607.01092","kind":"arxiv","version":1}},"canonical_sha256":"22603303dd9e3c92c7e378a3cacb299a71a59d6f040ff07437a51d9e770162d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22603303dd9e3c92c7e378a3cacb299a71a59d6f040ff07437a51d9e770162d9","first_computed_at":"2026-05-18T01:11:30.170370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:30.170370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YBujEuiH/8yFWP+ESxDLAhQqAa0fVRTuo9zf0GzLE6XvzY1sMJYbWBvp3G/40zOLd+qjW7saRbVBv92AF6srDA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:30.170709Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.01092","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0fdf4c9f52ffb0f529dc09279e84a6c1f340a6df51ad5ca5d27cbcd6c0236849","sha256:efeeadd1bcd2885e19b0e76120513c3b405f2b5007f0416da2d013c816990a3a"],"state_sha256":"c1d1b6745a65d4b043ad988afdf9c9fc8fdb28aa3dd222a4ddd387ede8654554"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rf8FNm3rpHg24huPBsEm9oki6f/WSR3usvZmO84uyaiYuCF9yUwYVJ84NPjvJ0kxdrgW8+utE3kZceqCKd9bDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T19:38:14.777799Z","bundle_sha256":"beb8bcb83fbb868e18d5bddb602d51d15b01c36c29dcadb3664d38457e270caa"}}