{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:AFIXOF3HJX2GAQ7TDFKZ4WONBJ","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":"4bfea6c54b932a4a93150b959365c147a19b1da6557eb27422545facbbd381d1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T18:10:16Z","title_canon_sha256":"9f439c8c4238b58c06d8a34bbfc4707abfaffbd1d0e57a0ce444abfb88c013c7"},"schema_version":"1.0","source":{"id":"1806.09648","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.09648","created_at":"2026-05-18T00:09:35Z"},{"alias_kind":"arxiv_version","alias_value":"1806.09648v2","created_at":"2026-05-18T00:09:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.09648","created_at":"2026-05-18T00:09:35Z"},{"alias_kind":"pith_short_12","alias_value":"AFIXOF3HJX2G","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"AFIXOF3HJX2GAQ7T","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"AFIXOF3H","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:b588e3bfd9cdca4dec84e1ca5caffbcdfcd5afd3a00fdce57cb6d9aadcb06b8b","target":"graph","created_at":"2026-05-18T00:09:35Z","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":"Detecting lesions from computed tomography (CT) scans is an important but difficult problem because non-lesions and true lesions can appear similar. 3D context is known to be helpful in this differentiation task. However, existing end-to-end detection frameworks of convolutional neural networks (CNNs) are mostly designed for 2D images. In this paper, we propose 3D context enhanced region-based CNN (3DCE) to incorporate 3D context information efficiently by aggregating feature maps of 2D images. 3DCE is easy to train and end-to-end in training and inference. A universal lesion detector is devel","authors_text":"Ke Yan, Mohammadhadi Bagheri, Ronald M. Summers","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T18:10:16Z","title":"3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.09648","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":"sha256:1b5fc310a46fa7eab06f19bb434b4fbf445ab6319deb9cb2a2e543c6ba1e1f39","target":"record","created_at":"2026-05-18T00:09:35Z","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":"4bfea6c54b932a4a93150b959365c147a19b1da6557eb27422545facbbd381d1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T18:10:16Z","title_canon_sha256":"9f439c8c4238b58c06d8a34bbfc4707abfaffbd1d0e57a0ce444abfb88c013c7"},"schema_version":"1.0","source":{"id":"1806.09648","kind":"arxiv","version":2}},"canonical_sha256":"01517717674df46043f319559e59cd0a6475cf064fb1faee558af1c7cf7ac39b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01517717674df46043f319559e59cd0a6475cf064fb1faee558af1c7cf7ac39b","first_computed_at":"2026-05-18T00:09:35.429744Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:35.429744Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sVZ54UC9mefkIrbkR/of7k0ugt22qEUUF+/s0iLyhvq6ohuRY6ONw95d60ECG2QZLGMzEP6ib0s+fq3ToBq4BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:35.430217Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.09648","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b5fc310a46fa7eab06f19bb434b4fbf445ab6319deb9cb2a2e543c6ba1e1f39","sha256:b588e3bfd9cdca4dec84e1ca5caffbcdfcd5afd3a00fdce57cb6d9aadcb06b8b"],"state_sha256":"47a69b6bb527d3d1e0d28c1e50d5fc7107f1a042f3451285094b0167b172dc77"}