{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:WQXCEHRC7GZZBW33PSKAW5P4K7","short_pith_number":"pith:WQXCEHRC","schema_version":"1.0","canonical_sha256":"b42e221e22f9b390db7b7c940b75fc57ee6a49dfd41ec7343f583fc567e5a066","source":{"kind":"arxiv","id":"2407.11401","version":1},"attestation_state":"computed","paper":{"title":"EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CV","authors_text":"Peiyao Fu, Pinghong Zhou, Quanlin Li, Ruijie Yang, Shuo Wang, Xian Yang, Yan Zhu, Yizhe Zhang, Zhihua Wang","submitted_at":"2024-07-16T05:40:17Z","abstract_excerpt":"Determining the necessity of resecting malignant polyps during colonoscopy screen is crucial for patient outcomes, yet challenging due to the time-consuming and costly nature of histopathology examination. While deep learning-based classification models have shown promise in achieving optical biopsy with endoscopic images, they often suffer from a lack of explainability. To overcome this limitation, we introduce EndoFinder, a content-based image retrieval framework to find the 'digital twin' polyp in the reference database given a newly detected polyp. The clinical semantics of the new polyp c"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2407.11401","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T05:40:17Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"e74817ab44c8d1eef42d1b6ecd80268a8e4987c789d633de668c6d9b99ec154e","abstract_canon_sha256":"43e126cbff270ac3ec087a1660d445ba9abfceb04d369dd732c94356c7f50f33"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:23.946285Z","signature_b64":"x/hZ/viULnVyDB6wRVj/WrEkp8EFZYJl5yGJ4+H8/LuyaB7DqoGepZiW2auslxbREy9OHUd7K11P/+c97W0WAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b42e221e22f9b390db7b7c940b75fc57ee6a49dfd41ec7343f583fc567e5a066","last_reissued_at":"2026-07-05T08:44:23.945872Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:23.945872Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CV","authors_text":"Peiyao Fu, Pinghong Zhou, Quanlin Li, Ruijie Yang, Shuo Wang, Xian Yang, Yan Zhu, Yizhe Zhang, Zhihua Wang","submitted_at":"2024-07-16T05:40:17Z","abstract_excerpt":"Determining the necessity of resecting malignant polyps during colonoscopy screen is crucial for patient outcomes, yet challenging due to the time-consuming and costly nature of histopathology examination. While deep learning-based classification models have shown promise in achieving optical biopsy with endoscopic images, they often suffer from a lack of explainability. To overcome this limitation, we introduce EndoFinder, a content-based image retrieval framework to find the 'digital twin' polyp in the reference database given a newly detected polyp. The clinical semantics of the new polyp c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11401","kind":"arxiv","version":1},"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/2407.11401/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2407.11401","created_at":"2026-07-05T08:44:23.945930+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.11401v1","created_at":"2026-07-05T08:44:23.945930+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11401","created_at":"2026-07-05T08:44:23.945930+00:00"},{"alias_kind":"pith_short_12","alias_value":"WQXCEHRC7GZZ","created_at":"2026-07-05T08:44:23.945930+00:00"},{"alias_kind":"pith_short_16","alias_value":"WQXCEHRC7GZZBW33","created_at":"2026-07-05T08:44:23.945930+00:00"},{"alias_kind":"pith_short_8","alias_value":"WQXCEHRC","created_at":"2026-07-05T08:44:23.945930+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.17323","citing_title":"EndoFinder: Online Lesion Retrieval for Explainable Colorectal Polyp Diagnosis Leveraging Latent Scene Representations","ref_index":39,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7","json":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7.json","graph_json":"https://pith.science/api/pith-number/WQXCEHRC7GZZBW33PSKAW5P4K7/graph.json","events_json":"https://pith.science/api/pith-number/WQXCEHRC7GZZBW33PSKAW5P4K7/events.json","paper":"https://pith.science/paper/WQXCEHRC"},"agent_actions":{"view_html":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7","download_json":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7.json","view_paper":"https://pith.science/paper/WQXCEHRC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.11401&json=true","fetch_graph":"https://pith.science/api/pith-number/WQXCEHRC7GZZBW33PSKAW5P4K7/graph.json","fetch_events":"https://pith.science/api/pith-number/WQXCEHRC7GZZBW33PSKAW5P4K7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7/action/storage_attestation","attest_author":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7/action/author_attestation","sign_citation":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7/action/citation_signature","submit_replication":"https://pith.science/pith/WQXCEHRC7GZZBW33PSKAW5P4K7/action/replication_record"}},"created_at":"2026-07-05T08:44:23.945930+00:00","updated_at":"2026-07-05T08:44:23.945930+00:00"}