{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:VJ3K2XTQLQGQPBGJHQERSOFAW3","short_pith_number":"pith:VJ3K2XTQ","canonical_record":{"source":{"id":"1808.01944","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2018-08-06T14:51:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"ab7b599bbf6e61b1480ce121da18ff7d0b30f81183a508cc66d751658d1bcefb","abstract_canon_sha256":"b75cc1c6d46daeb5e8b610d3e5e3d08749e114a3e02e0a00bc9c7bf1edae38e6"},"schema_version":"1.0"},"canonical_sha256":"aa76ad5e705c0d0784c93c091938a0b6f65f187af13ba15953ce48cb61d0c8c6","source":{"kind":"arxiv","id":"1808.01944","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.01944","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"arxiv_version","alias_value":"1808.01944v2","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.01944","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"pith_short_12","alias_value":"VJ3K2XTQLQGQ","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"VJ3K2XTQLQGQPBGJ","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"VJ3K2XTQ","created_at":"2026-05-18T12:32:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:VJ3K2XTQLQGQPBGJHQERSOFAW3","target":"record","payload":{"canonical_record":{"source":{"id":"1808.01944","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2018-08-06T14:51:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"ab7b599bbf6e61b1480ce121da18ff7d0b30f81183a508cc66d751658d1bcefb","abstract_canon_sha256":"b75cc1c6d46daeb5e8b610d3e5e3d08749e114a3e02e0a00bc9c7bf1edae38e6"},"schema_version":"1.0"},"canonical_sha256":"aa76ad5e705c0d0784c93c091938a0b6f65f187af13ba15953ce48cb61d0c8c6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:39.158357Z","signature_b64":"HwGTi1dddRy53HCyYoNUi9zM/sjqsJcl5D5kqSBzOHQFZ0IBCTd7O6KVwiLe5MJRiQYLYqDrxfEHmOwJZr61Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa76ad5e705c0d0784c93c091938a0b6f65f187af13ba15953ce48cb61d0c8c6","last_reissued_at":"2026-05-18T00:04:39.157872Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:39.157872Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.01944","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:04:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3XnTg5Ykh9ked5jQmkUKuF8o9Pys+Xhs6m15PpqRfwuMKiq2hc3UbAYgwVTSscZhpUzn6ck7cOOLqCZR2FzEBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T07:58:02.628974Z"},"content_sha256":"074144c2d21a74a1dccd028c8d8ec3ca97606e1585d59689ef120320cb49d2ac","schema_version":"1.0","event_id":"sha256:074144c2d21a74a1dccd028c8d8ec3ca97606e1585d59689ef120320cb49d2ac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:VJ3K2XTQLQGQPBGJHQERSOFAW3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Giovanni Montana, Nicol\\'o Savioli, Pablo Lamata","submitted_at":"2018-08-06T14:51:33Z","abstract_excerpt":"Atrial Fibrillation (AF) is a common electro-physiological cardiac disorder that causes changes in the anatomy of the atria. A better characterization of these changes is desirable for the definition of clinical biomarkers, furthermore, thus there is a need for its fully automatic segmentation from clinical images. In this work, we present an architecture based on 3D-convolution kernels, a Volumetric Fully Convolution Neural Network (V-FCNN), able to segment the entire volume in a one-shot, and consequently integrate the implicit spatial redundancy present in high-resolution images. A loss fun"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.01944","kind":"arxiv","version":2},"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":"2026-05-18T00:04:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MlL1yyvoVJjFS+vRP9HeXjO2J0jOd9wgJ+VfP1YjdIAgrPzYWBxOuPu67YQ6PSzOYxgvem3VOft2YgsY9Y3UCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T07:58:02.629344Z"},"content_sha256":"3c0a880ebd2c7f8cafe86c07f9a01f6d299d4a081c9f5b8992018752f582599f","schema_version":"1.0","event_id":"sha256:3c0a880ebd2c7f8cafe86c07f9a01f6d299d4a081c9f5b8992018752f582599f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/bundle.json","state_url":"https://pith.science/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/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":"2026-06-03T07:58:02Z","links":{"resolver":"https://pith.science/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3","bundle":"https://pith.science/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/bundle.json","state":"https://pith.science/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJ3K2XTQLQGQPBGJHQERSOFAW3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:VJ3K2XTQLQGQPBGJHQERSOFAW3","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":"b75cc1c6d46daeb5e8b610d3e5e3d08749e114a3e02e0a00bc9c7bf1edae38e6","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2018-08-06T14:51:33Z","title_canon_sha256":"ab7b599bbf6e61b1480ce121da18ff7d0b30f81183a508cc66d751658d1bcefb"},"schema_version":"1.0","source":{"id":"1808.01944","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.01944","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"arxiv_version","alias_value":"1808.01944v2","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.01944","created_at":"2026-05-18T00:04:39Z"},{"alias_kind":"pith_short_12","alias_value":"VJ3K2XTQLQGQ","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"VJ3K2XTQLQGQPBGJ","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"VJ3K2XTQ","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:3c0a880ebd2c7f8cafe86c07f9a01f6d299d4a081c9f5b8992018752f582599f","target":"graph","created_at":"2026-05-18T00:04:39Z","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":"Atrial Fibrillation (AF) is a common electro-physiological cardiac disorder that causes changes in the anatomy of the atria. A better characterization of these changes is desirable for the definition of clinical biomarkers, furthermore, thus there is a need for its fully automatic segmentation from clinical images. In this work, we present an architecture based on 3D-convolution kernels, a Volumetric Fully Convolution Neural Network (V-FCNN), able to segment the entire volume in a one-shot, and consequently integrate the implicit spatial redundancy present in high-resolution images. A loss fun","authors_text":"Giovanni Montana, Nicol\\'o Savioli, Pablo Lamata","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2018-08-06T14:51:33Z","title":"V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.01944","kind":"arxiv","version":2},"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":"sha256:074144c2d21a74a1dccd028c8d8ec3ca97606e1585d59689ef120320cb49d2ac","target":"record","created_at":"2026-05-18T00:04:39Z","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":"b75cc1c6d46daeb5e8b610d3e5e3d08749e114a3e02e0a00bc9c7bf1edae38e6","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2018-08-06T14:51:33Z","title_canon_sha256":"ab7b599bbf6e61b1480ce121da18ff7d0b30f81183a508cc66d751658d1bcefb"},"schema_version":"1.0","source":{"id":"1808.01944","kind":"arxiv","version":2}},"canonical_sha256":"aa76ad5e705c0d0784c93c091938a0b6f65f187af13ba15953ce48cb61d0c8c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa76ad5e705c0d0784c93c091938a0b6f65f187af13ba15953ce48cb61d0c8c6","first_computed_at":"2026-05-18T00:04:39.157872Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:39.157872Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HwGTi1dddRy53HCyYoNUi9zM/sjqsJcl5D5kqSBzOHQFZ0IBCTd7O6KVwiLe5MJRiQYLYqDrxfEHmOwJZr61Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:39.158357Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.01944","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:074144c2d21a74a1dccd028c8d8ec3ca97606e1585d59689ef120320cb49d2ac","sha256:3c0a880ebd2c7f8cafe86c07f9a01f6d299d4a081c9f5b8992018752f582599f"],"state_sha256":"c3884b55a4fadff9c3ef2cf179dd0a330271c64ba230cd4da6eea2f4c588ffb5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rq4DDWnveVHWth7E+EDtBFo2kPvhUAMGfddxftDu2dNZ6eTtec71Im/2l5xgvLiNfASGvU+Ew6SD99ICbgPoAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T07:58:02.632055Z","bundle_sha256":"d74ed0aa6439e9427259b0413bd2626b6eebdc3ee572ddf8cff259794a6daaf6"}}