{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:VNOT6WFXMSBIMIYX3B67UUPTLB","short_pith_number":"pith:VNOT6WFX","canonical_record":{"source":{"id":"2001.04537","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-01-13T21:37:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"7981a93dff77ee1f315c17d6e4acf9eb14de17147c1e84863173faf9ab16e34c","abstract_canon_sha256":"3ac587f9d70bfdaea930abe1ace71cb450b0ae398f35a0d9222258f223e94549"},"schema_version":"1.0"},"canonical_sha256":"ab5d3f58b76482862317d87dfa51f35864b07e08b6be3876938d2c20a85a4f33","source":{"kind":"arxiv","id":"2001.04537","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.04537","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"arxiv_version","alias_value":"2001.04537v3","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.04537","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_12","alias_value":"VNOT6WFXMSBI","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_16","alias_value":"VNOT6WFXMSBIMIYX","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_8","alias_value":"VNOT6WFX","created_at":"2026-07-05T02:46:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:VNOT6WFXMSBIMIYX3B67UUPTLB","target":"record","payload":{"canonical_record":{"source":{"id":"2001.04537","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-01-13T21:37:33Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"7981a93dff77ee1f315c17d6e4acf9eb14de17147c1e84863173faf9ab16e34c","abstract_canon_sha256":"3ac587f9d70bfdaea930abe1ace71cb450b0ae398f35a0d9222258f223e94549"},"schema_version":"1.0"},"canonical_sha256":"ab5d3f58b76482862317d87dfa51f35864b07e08b6be3876938d2c20a85a4f33","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:46:57.878756Z","signature_b64":"mOanGbHIQXtrFWgT74vYry2OvvUMCzTNMxTeIrSzMg15RceXPmTsSs/sxvvg0hMEan3/MdC8fWwvuOeJaFjgAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab5d3f58b76482862317d87dfa51f35864b07e08b6be3876938d2c20a85a4f33","last_reissued_at":"2026-07-05T02:46:57.878294Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:46:57.878294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2001.04537","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:46:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jscq5P7yjq7bH746A2oHn4PGkxk1Hq3MIZWMR5h+b+5a57Wg6UacYV+kKjE0wncladx8Ji8QpcD1jkV1Y66rDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T01:15:26.615255Z"},"content_sha256":"e5437abce5af6e39528c92ef8eb8cd0fda65860ebc1df2ce8db7761760d08a19","schema_version":"1.0","event_id":"sha256:e5437abce5af6e39528c92ef8eb8cd0fda65860ebc1df2ce8db7761760d08a19"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:VNOT6WFXMSBIMIYX3B67UUPTLB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep convolutional neural networks for multi-planar lung nodule detection: improvement in small nodule identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Ludo J. Cornelissen, Matthijs Oudkerk, Peter M.A. van Ooijen, Raymond N. J. Veldhuis, Sunyi Zheng, Xiaonan Cui, Xueping Jing","submitted_at":"2020-01-13T21:37:33Z","abstract_excerpt":"Objective: In clinical practice, small lung nodules can be easily overlooked by radiologists. The paper aims to provide an efficient and accurate detection system for small lung nodules while keeping good performance for large nodules. Methods: We propose a multi-planar detection system using convolutional neural networks. The 2-D convolutional neural network model, U-net++, was trained by axial, coronal, and sagittal slices for the candidate detection task. All possible nodule candidates from the three different planes are combined. For false positive reduction, we apply 3-D multi-scale dense"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.04537","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2001.04537/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T02:46:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZieiVZ1yNmWe6zdO2+cn29O6YojBqtjm2STf4krp/tCUrVdoNz8MZvGUqEPYCAW4kCRRWmCxAOFEEKwSnwwJDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T01:15:26.615762Z"},"content_sha256":"dd30c54d9808a65146c1fd7c446ac392c9a8ec25f1d4e3c2a6246be4e1ec87e6","schema_version":"1.0","event_id":"sha256:dd30c54d9808a65146c1fd7c446ac392c9a8ec25f1d4e3c2a6246be4e1ec87e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/bundle.json","state_url":"https://pith.science/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/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":"2026-08-24T01:15:26Z","links":{"resolver":"https://pith.science/pith/VNOT6WFXMSBIMIYX3B67UUPTLB","bundle":"https://pith.science/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/bundle.json","state":"https://pith.science/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VNOT6WFXMSBIMIYX3B67UUPTLB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:VNOT6WFXMSBIMIYX3B67UUPTLB","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":"3ac587f9d70bfdaea930abe1ace71cb450b0ae398f35a0d9222258f223e94549","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-01-13T21:37:33Z","title_canon_sha256":"7981a93dff77ee1f315c17d6e4acf9eb14de17147c1e84863173faf9ab16e34c"},"schema_version":"1.0","source":{"id":"2001.04537","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.04537","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"arxiv_version","alias_value":"2001.04537v3","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.04537","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_12","alias_value":"VNOT6WFXMSBI","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_16","alias_value":"VNOT6WFXMSBIMIYX","created_at":"2026-07-05T02:46:57Z"},{"alias_kind":"pith_short_8","alias_value":"VNOT6WFX","created_at":"2026-07-05T02:46:57Z"}],"graph_snapshots":[{"event_id":"sha256:dd30c54d9808a65146c1fd7c446ac392c9a8ec25f1d4e3c2a6246be4e1ec87e6","target":"graph","created_at":"2026-07-05T02:46:57Z","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/2001.04537/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Objective: In clinical practice, small lung nodules can be easily overlooked by radiologists. The paper aims to provide an efficient and accurate detection system for small lung nodules while keeping good performance for large nodules. Methods: We propose a multi-planar detection system using convolutional neural networks. The 2-D convolutional neural network model, U-net++, was trained by axial, coronal, and sagittal slices for the candidate detection task. All possible nodule candidates from the three different planes are combined. For false positive reduction, we apply 3-D multi-scale dense","authors_text":"Ludo J. Cornelissen, Matthijs Oudkerk, Peter M.A. van Ooijen, Raymond N. J. Veldhuis, Sunyi Zheng, Xiaonan Cui, Xueping Jing","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-01-13T21:37:33Z","title":"Deep convolutional neural networks for multi-planar lung nodule detection: improvement in small nodule identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.04537","kind":"arxiv","version":3},"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:e5437abce5af6e39528c92ef8eb8cd0fda65860ebc1df2ce8db7761760d08a19","target":"record","created_at":"2026-07-05T02:46:57Z","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":"3ac587f9d70bfdaea930abe1ace71cb450b0ae398f35a0d9222258f223e94549","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-01-13T21:37:33Z","title_canon_sha256":"7981a93dff77ee1f315c17d6e4acf9eb14de17147c1e84863173faf9ab16e34c"},"schema_version":"1.0","source":{"id":"2001.04537","kind":"arxiv","version":3}},"canonical_sha256":"ab5d3f58b76482862317d87dfa51f35864b07e08b6be3876938d2c20a85a4f33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab5d3f58b76482862317d87dfa51f35864b07e08b6be3876938d2c20a85a4f33","first_computed_at":"2026-07-05T02:46:57.878294Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:46:57.878294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mOanGbHIQXtrFWgT74vYry2OvvUMCzTNMxTeIrSzMg15RceXPmTsSs/sxvvg0hMEan3/MdC8fWwvuOeJaFjgAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:46:57.878756Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.04537","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e5437abce5af6e39528c92ef8eb8cd0fda65860ebc1df2ce8db7761760d08a19","sha256:dd30c54d9808a65146c1fd7c446ac392c9a8ec25f1d4e3c2a6246be4e1ec87e6"],"state_sha256":"38947e5d41eaf48ac728f8edbac1ad6fa06eda313f26222f998385c6bcf8e026"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"48AypIv+xyCnzxCCBLkNz/1z0wGoNHjEDBMTpBLfB7pR9l3QAUBkqYGN4qaKeZMNCFCXaAoOf1ikXb6uwzUxBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-24T01:15:26.619757Z","bundle_sha256":"d2929c392f3d774f650aab3cc1c0419b561ae4fbb0e064fb6e14c3db99772e34"}}