{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:B2CIPQPYZS7CRKZMVNPEE6OT33","short_pith_number":"pith:B2CIPQPY","canonical_record":{"source":{"id":"1812.02518","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-06T13:34:24Z","cross_cats_sorted":[],"title_canon_sha256":"26e5cdf9e0d691bea22b0120f0340fdef47edfb4a1270f2a7ac64185a4262784","abstract_canon_sha256":"5ffac18a6fc920631f9a2355730d455b88814ada3106d5582ef7cf682d643311"},"schema_version":"1.0"},"canonical_sha256":"0e8487c1f8ccbe28ab2cab5e4279d3def1784617bdbdd6ade9a82f6669311c49","source":{"kind":"arxiv","id":"1812.02518","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.02518","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"arxiv_version","alias_value":"1812.02518v1","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.02518","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"pith_short_12","alias_value":"B2CIPQPYZS7C","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B2CIPQPYZS7CRKZM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B2CIPQPY","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:B2CIPQPYZS7CRKZMVNPEE6OT33","target":"record","payload":{"canonical_record":{"source":{"id":"1812.02518","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-06T13:34:24Z","cross_cats_sorted":[],"title_canon_sha256":"26e5cdf9e0d691bea22b0120f0340fdef47edfb4a1270f2a7ac64185a4262784","abstract_canon_sha256":"5ffac18a6fc920631f9a2355730d455b88814ada3106d5582ef7cf682d643311"},"schema_version":"1.0"},"canonical_sha256":"0e8487c1f8ccbe28ab2cab5e4279d3def1784617bdbdd6ade9a82f6669311c49","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:55.504851Z","signature_b64":"ODJ9gmyh4KnWe5etyQxZvMb8q3QiAipfg150J5ZBSghGRhe1wxV3GdPSy1fhlP5wqtjxJQSFBOV2dH+MIH8nBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e8487c1f8ccbe28ab2cab5e4279d3def1784617bdbdd6ade9a82f6669311c49","last_reissued_at":"2026-05-17T23:58:55.504403Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:55.504403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.02518","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":"2026-05-17T23:58:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EAM+Hw3izo9UWjpzRHUjjhrUK8rpXv4VkVgSMWFer9L7hSZcqwwECSp+oH/0CmxD4NiIidhZLtJkOSOPIYNgDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:23:07.146127Z"},"content_sha256":"775a63c94beb5123ae1ce44b9494b49448d74f9b89b3cd79e7ad5d590a26ae08","schema_version":"1.0","event_id":"sha256:775a63c94beb5123ae1ce44b9494b49448d74f9b89b3cd79e7ad5d590a26ae08"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:B2CIPQPYZS7CRKZMVNPEE6OT33","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Antoine Despinasse, Herv\\'e Delingette, Hubert Cochet, Maxime Sermesant, Pierre Ja\\\"is, Shuman Jia, Xavier Pennec, Zihao Wang","submitted_at":"2018-12-06T13:34:24Z","abstract_excerpt":"Radiological imaging offers effective measurement of anatomy, which is useful in disease diagnosis and assessment. Previous study has shown that the left atrial wall remodeling can provide information to predict treatment outcome in atrial fibrillation. Nevertheless, the segmentation of the left atrial structures from medical images is still very time-consuming. Current advances in neural network may help creating automatic segmentation models that reduce the workload for clinicians. In this preliminary study, we propose automated, two-stage, three-dimensional U-Nets with convolutional neural "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.02518","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":"2026-05-17T23:58:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O5Kw+AZRO/RLJISaEiRao20KnKgzsbi191vF+zSV74B2JoCd/JwNMMB/8hNjhfmc4E5AcxmBNdBNUmVPoztdBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:23:07.146791Z"},"content_sha256":"255fb28108e3bd4f3c6776ce064a63e6293fc3343f9c6c3f3c9ac867c1d6e63b","schema_version":"1.0","event_id":"sha256:255fb28108e3bd4f3c6776ce064a63e6293fc3343f9c6c3f3c9ac867c1d6e63b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/bundle.json","state_url":"https://pith.science/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/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":"2026-05-26T15:23:07Z","links":{"resolver":"https://pith.science/pith/B2CIPQPYZS7CRKZMVNPEE6OT33","bundle":"https://pith.science/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/bundle.json","state":"https://pith.science/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B2CIPQPYZS7CRKZMVNPEE6OT33/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:B2CIPQPYZS7CRKZMVNPEE6OT33","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":"5ffac18a6fc920631f9a2355730d455b88814ada3106d5582ef7cf682d643311","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-06T13:34:24Z","title_canon_sha256":"26e5cdf9e0d691bea22b0120f0340fdef47edfb4a1270f2a7ac64185a4262784"},"schema_version":"1.0","source":{"id":"1812.02518","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.02518","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"arxiv_version","alias_value":"1812.02518v1","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.02518","created_at":"2026-05-17T23:58:55Z"},{"alias_kind":"pith_short_12","alias_value":"B2CIPQPYZS7C","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B2CIPQPYZS7CRKZM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B2CIPQPY","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:255fb28108e3bd4f3c6776ce064a63e6293fc3343f9c6c3f3c9ac867c1d6e63b","target":"graph","created_at":"2026-05-17T23:58:55Z","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":"Radiological imaging offers effective measurement of anatomy, which is useful in disease diagnosis and assessment. Previous study has shown that the left atrial wall remodeling can provide information to predict treatment outcome in atrial fibrillation. Nevertheless, the segmentation of the left atrial structures from medical images is still very time-consuming. Current advances in neural network may help creating automatic segmentation models that reduce the workload for clinicians. In this preliminary study, we propose automated, two-stage, three-dimensional U-Nets with convolutional neural ","authors_text":"Antoine Despinasse, Herv\\'e Delingette, Hubert Cochet, Maxime Sermesant, Pierre Ja\\\"is, Shuman Jia, Xavier Pennec, Zihao Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-06T13:34:24Z","title":"Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.02518","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":"sha256:775a63c94beb5123ae1ce44b9494b49448d74f9b89b3cd79e7ad5d590a26ae08","target":"record","created_at":"2026-05-17T23:58:55Z","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":"5ffac18a6fc920631f9a2355730d455b88814ada3106d5582ef7cf682d643311","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-06T13:34:24Z","title_canon_sha256":"26e5cdf9e0d691bea22b0120f0340fdef47edfb4a1270f2a7ac64185a4262784"},"schema_version":"1.0","source":{"id":"1812.02518","kind":"arxiv","version":1}},"canonical_sha256":"0e8487c1f8ccbe28ab2cab5e4279d3def1784617bdbdd6ade9a82f6669311c49","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e8487c1f8ccbe28ab2cab5e4279d3def1784617bdbdd6ade9a82f6669311c49","first_computed_at":"2026-05-17T23:58:55.504403Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:55.504403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ODJ9gmyh4KnWe5etyQxZvMb8q3QiAipfg150J5ZBSghGRhe1wxV3GdPSy1fhlP5wqtjxJQSFBOV2dH+MIH8nBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:55.504851Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.02518","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:775a63c94beb5123ae1ce44b9494b49448d74f9b89b3cd79e7ad5d590a26ae08","sha256:255fb28108e3bd4f3c6776ce064a63e6293fc3343f9c6c3f3c9ac867c1d6e63b"],"state_sha256":"6e2606f95b523ce94c4aad11c639a66b6981e64f4c3d270f5ecaa2ac112dbbd8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AKKHHmB94/uB4P9o8jp3/4/2eB8itQdTIdKNpJh0r4u7uF8rRUtADznKBsRdZ62Gf/k0A6uuHc52LdPHcLclDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T15:23:07.150039Z","bundle_sha256":"d03a039020195714bf9f2e3bdb615d9a3039b7a22dbc1f0631e238a276df7f5d"}}