{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WYZEZ36EYQ5USQVJEYHMGEVL3X","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":"89314028012130a5b56bafdd941cf3933549b989167ef9d1ec09941006b31cd6","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-30T05:55:45Z","title_canon_sha256":"c5b828c510262dab15f801abaafeb86a9c85e1f581d6442dc08881d5c25e9092"},"schema_version":"1.0","source":{"id":"2211.00003","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00003","created_at":"2026-07-05T05:28:09Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00003v2","created_at":"2026-07-05T05:28:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00003","created_at":"2026-07-05T05:28:09Z"},{"alias_kind":"pith_short_12","alias_value":"WYZEZ36EYQ5U","created_at":"2026-07-05T05:28:09Z"},{"alias_kind":"pith_short_16","alias_value":"WYZEZ36EYQ5USQVJ","created_at":"2026-07-05T05:28:09Z"},{"alias_kind":"pith_short_8","alias_value":"WYZEZ36E","created_at":"2026-07-05T05:28:09Z"}],"graph_snapshots":[{"event_id":"sha256:a86f68770ce0dc3f6832cbfe83b15735e50796ad44ce81fcf8dbea140c324181","target":"graph","created_at":"2026-07-05T05:28:09Z","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/2211.00003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this study, we propose a lung nodule detection scheme which fully incorporates the clinic workflow of radiologists. Particularly, we exploit Bi-Directional Maximum intensity projection (MIP) images of various thicknesses (i.e., 3, 5 and 10mm) along with a 3D patch of CT scan, consisting of 10 adjacent slices to feed into self-distillation-based Multi-Encoders Network (MEDS-Net). The proposed architecture first condenses 3D patch input to three channels by using a dense block which consists of dense units which effectively examine the nodule presence from 2D axial slices. This condensed info","authors_text":"Abdullah Shahid, Azka Rehman, Byoung Dai Lee, Byung il Lee, Muhammad Usman, Shi Sub Byon, Siddique Latif, Sung Hyun Kim, Yeong Gil Shin","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-30T05:55:45Z","title":"MEDS-Net: Self-Distilled Multi-Encoders Network with Bi-Direction Maximum Intensity projections for Lung Nodule Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00003","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":"sha256:6eac627aa94141a5918aa1fa3dbe9c52fbd0feb388651a9177b25b74bc78601f","target":"record","created_at":"2026-07-05T05:28:09Z","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":"89314028012130a5b56bafdd941cf3933549b989167ef9d1ec09941006b31cd6","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-10-30T05:55:45Z","title_canon_sha256":"c5b828c510262dab15f801abaafeb86a9c85e1f581d6442dc08881d5c25e9092"},"schema_version":"1.0","source":{"id":"2211.00003","kind":"arxiv","version":2}},"canonical_sha256":"b6324cefc4c43b4942a9260ec312abddff7bf3e32bc32fbaff99470c21a9867b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6324cefc4c43b4942a9260ec312abddff7bf3e32bc32fbaff99470c21a9867b","first_computed_at":"2026-07-05T05:28:09.594899Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:28:09.594899Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pfVen1RlWCvt1p45rTXh0xBBc2B1a6oAYITfkWKlujMvqb8SvPQGHTHf520+C64G0SrZV1vmGl4w6QeoSqB2Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:28:09.595356Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.00003","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6eac627aa94141a5918aa1fa3dbe9c52fbd0feb388651a9177b25b74bc78601f","sha256:a86f68770ce0dc3f6832cbfe83b15735e50796ad44ce81fcf8dbea140c324181"],"state_sha256":"d1613d0cdab29efdefdbe7247e5ef7dd7ee333c65601444fdb67b2b0014f83fe"}