{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:APOHT7C4EO3J4HSO2SVUMOAVOZ","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":"3ab2e0d484eff3020cd39be3b6f68ab2df478eb10595f7b3ea9c120ef972dd04","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-31T14:17:36Z","title_canon_sha256":"8315e390d185f24c1da2b4cea43b637b11b81211387c24191f78a37e9627f348"},"schema_version":"1.0","source":{"id":"1901.11369","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.11369","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"arxiv_version","alias_value":"1901.11369v2","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.11369","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"pith_short_12","alias_value":"APOHT7C4EO3J","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"APOHT7C4EO3J4HSO","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"APOHT7C4","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:44d1c8cd03f1a5be9d506b9479a54ddf3764effcd24ece06e12cf7484670da79","target":"graph","created_at":"2026-05-17T23:39:30Z","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":"Lack of large expert annotated MR datasets makes training deep learning models difficult. Therefore, a cross-modality (MR-CT) deep learning segmentation approach that augments training data using pseudo MR images produced by transforming expert-segmented CT images was developed. Eighty-One T2-weighted MRI scans from 28 patients with non-small cell lung cancers were analyzed. Cross-modality prior encoding the transformation of CT to pseudo MR images resembling T2w MRI was learned as a generative adversarial deep learning model. This model augmented training data arising from 6 expert-segmented ","authors_text":"Andreas Rimner, Harini Veeraraghavan, Joseph O. Deasy, Jue Jiang, Neelam Tyagi, Pengpeng Zhang, Yu-Chi Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-31T14:17:36Z","title":"Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.11369","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:ff9e7758ab68160305c4d87c8adda7e87e3ccbf35a1c9db0ece59ac609d4b794","target":"record","created_at":"2026-05-17T23:39:30Z","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":"3ab2e0d484eff3020cd39be3b6f68ab2df478eb10595f7b3ea9c120ef972dd04","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-31T14:17:36Z","title_canon_sha256":"8315e390d185f24c1da2b4cea43b637b11b81211387c24191f78a37e9627f348"},"schema_version":"1.0","source":{"id":"1901.11369","kind":"arxiv","version":2}},"canonical_sha256":"03dc79fc5c23b69e1e4ed4ab46381576458fc623768cc15ad5d9e64d5bb3952c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03dc79fc5c23b69e1e4ed4ab46381576458fc623768cc15ad5d9e64d5bb3952c","first_computed_at":"2026-05-17T23:39:30.472208Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:30.472208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tsWsMx7UK1nl3gwWwndZiMEda3fB+IO4N5Gm9gFTkpE5L/hSSSpOfgxd9c5JAD91Ucu3hoGzF2Nrpupcpm04Dg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:30.472864Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.11369","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff9e7758ab68160305c4d87c8adda7e87e3ccbf35a1c9db0ece59ac609d4b794","sha256:44d1c8cd03f1a5be9d506b9479a54ddf3764effcd24ece06e12cf7484670da79"],"state_sha256":"6dccd96ac6b1eb2a59ac600c4783f86378d69d991214b5579f17665707056fb5"}