{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:CRNEUSQKBWJEF5IKA37CPBH2BA","short_pith_number":"pith:CRNEUSQK","schema_version":"1.0","canonical_sha256":"145a4a4a0a0d9242f50a06fe2784fa082f74cc69b6c587b6f5d3e230f0a71718","source":{"kind":"arxiv","id":"1901.03326","version":1},"attestation_state":"computed","paper":{"title":"High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"eess.IV","authors_text":"Alejandro F. Frangi, Ali Gooya, Le Zhang, Marco Pereanez, Rahman Attar, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Xenia Alba","submitted_at":"2019-01-10T12:35:50Z","abstract_excerpt":"The exploitation of large-scale population data has the potential to improve healthcare by discovering and understanding patterns and trends within this data. To enable high throughput analysis of cardiac imaging data automatically, a pipeline should comprise quality monitoring of the input images, segmentation of the cardiac structures, assessment of the segmentation quality, and parsing of cardiac functional indexes. We present a fully automatic, high throughput image parsing workflow for the analysis of cardiac MR images, and test its performance on the UK Biobank (UKB) cardiac dataset. The"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1901.03326","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-01-10T12:35:50Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"e35f8e8d123f2cc06f296f7775674dfd6292c2d49f501508854145d763d14919","abstract_canon_sha256":"067701eeda1bd58d385df881e5c16c5c5db7fd04119286388cd713373cf954fe"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:33.115952Z","signature_b64":"4pTxQeYLI9uLIG9uI+70/VfgNRfGv6ald38u6tF+zGAFEpQfPv5m+lEl/h9hFN/bLAFoCmlD5zZ/lNWxEAokCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"145a4a4a0a0d9242f50a06fe2784fa082f74cc69b6c587b6f5d3e230f0a71718","last_reissued_at":"2026-05-17T23:56:33.115420Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:33.115420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"eess.IV","authors_text":"Alejandro F. Frangi, Ali Gooya, Le Zhang, Marco Pereanez, Rahman Attar, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Xenia Alba","submitted_at":"2019-01-10T12:35:50Z","abstract_excerpt":"The exploitation of large-scale population data has the potential to improve healthcare by discovering and understanding patterns and trends within this data. To enable high throughput analysis of cardiac imaging data automatically, a pipeline should comprise quality monitoring of the input images, segmentation of the cardiac structures, assessment of the segmentation quality, and parsing of cardiac functional indexes. We present a fully automatic, high throughput image parsing workflow for the analysis of cardiac MR images, and test its performance on the UK Biobank (UKB) cardiac dataset. The"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03326","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1901.03326","created_at":"2026-05-17T23:56:33.115495+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.03326v1","created_at":"2026-05-17T23:56:33.115495+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03326","created_at":"2026-05-17T23:56:33.115495+00:00"},{"alias_kind":"pith_short_12","alias_value":"CRNEUSQKBWJE","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"CRNEUSQKBWJEF5IK","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"CRNEUSQK","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA","json":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA.json","graph_json":"https://pith.science/api/pith-number/CRNEUSQKBWJEF5IKA37CPBH2BA/graph.json","events_json":"https://pith.science/api/pith-number/CRNEUSQKBWJEF5IKA37CPBH2BA/events.json","paper":"https://pith.science/paper/CRNEUSQK"},"agent_actions":{"view_html":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA","download_json":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA.json","view_paper":"https://pith.science/paper/CRNEUSQK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.03326&json=true","fetch_graph":"https://pith.science/api/pith-number/CRNEUSQKBWJEF5IKA37CPBH2BA/graph.json","fetch_events":"https://pith.science/api/pith-number/CRNEUSQKBWJEF5IKA37CPBH2BA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA/action/storage_attestation","attest_author":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA/action/author_attestation","sign_citation":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA/action/citation_signature","submit_replication":"https://pith.science/pith/CRNEUSQKBWJEF5IKA37CPBH2BA/action/replication_record"}},"created_at":"2026-05-17T23:56:33.115495+00:00","updated_at":"2026-05-17T23:56:33.115495+00:00"}