{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:67AD2FEFRICH7NLXK6D2OTLIZT","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":"6a4d72b9ee96cb3e04ff5dd1b6dc738dc0182767eaaa0c66c05087735b5d6a1f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-14T19:25:56Z","title_canon_sha256":"664378ae7c8bc610b2c744d3e3aa1b995795dae884da787efebe5e8284eb3f38"},"schema_version":"1.0","source":{"id":"2210.08068","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.08068","created_at":"2026-07-05T05:07:06Z"},{"alias_kind":"arxiv_version","alias_value":"2210.08068v1","created_at":"2026-07-05T05:07:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.08068","created_at":"2026-07-05T05:07:06Z"},{"alias_kind":"pith_short_12","alias_value":"67AD2FEFRICH","created_at":"2026-07-05T05:07:06Z"},{"alias_kind":"pith_short_16","alias_value":"67AD2FEFRICH7NLX","created_at":"2026-07-05T05:07:06Z"},{"alias_kind":"pith_short_8","alias_value":"67AD2FEF","created_at":"2026-07-05T05:07:06Z"}],"graph_snapshots":[{"event_id":"sha256:a77ec7f0df8852506d767d307527d2684060a544ffb6d40b466e6ad3eed627c7","target":"graph","created_at":"2026-07-05T05:07:06Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2210.08068/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Background: A crucial initial processing step for quantitative PET/CT analysis is the segmentation of tumor lesions enabling accurate feature ex-traction, tumor characterization, oncologic staging, and image-based therapy response assessment. Manual lesion segmentation is however associated with enormous effort and cost and is thus infeasible in clinical routine. Goal: The goal of this study was to report the performance of a deep neural network designed to automatically segment regions suspected of cancer in whole-body 18F-FDG PET/CT images in the context of the AutoPET challenge. Method: A c","authors_text":"Lei Xiang, Ludovic Sibille, Xinrui Zhan","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-14T19:25:56Z","title":"Whole-body tumor segmentation of 18F -FDG PET/CT using a cascaded and ensembled convolutional neural networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.08068","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":"sha256:86653f4de10a973b213b72a6fc3d4213eaea37786c56bae68511b3e7b5457f70","target":"record","created_at":"2026-07-05T05:07:06Z","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":"6a4d72b9ee96cb3e04ff5dd1b6dc738dc0182767eaaa0c66c05087735b5d6a1f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-14T19:25:56Z","title_canon_sha256":"664378ae7c8bc610b2c744d3e3aa1b995795dae884da787efebe5e8284eb3f38"},"schema_version":"1.0","source":{"id":"2210.08068","kind":"arxiv","version":1}},"canonical_sha256":"f7c03d14858a047fb5775787a74d68ccc1de71a18b46a247974389eba3810e5b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f7c03d14858a047fb5775787a74d68ccc1de71a18b46a247974389eba3810e5b","first_computed_at":"2026-07-05T05:07:06.576153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:07:06.576153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uW1GudVLoTy6gEhuUTeZiRKhyoKjhrjHPLWIS8tROtOJJuxbC3ScSAuA4ak2uXSffdeveNQTE6qfDMHxmxcxBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:07:06.576633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.08068","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:86653f4de10a973b213b72a6fc3d4213eaea37786c56bae68511b3e7b5457f70","sha256:a77ec7f0df8852506d767d307527d2684060a544ffb6d40b466e6ad3eed627c7"],"state_sha256":"5d0aaa22ab17afde454c6f1fff234d97e65bed27ee6429d5e8a44339aba72511"}