{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:HJ6PMNNK6TK2IGIELR5H6TMY7R","short_pith_number":"pith:HJ6PMNNK","schema_version":"1.0","canonical_sha256":"3a7cf635aaf4d5a419045c7a7f4d98fc71e8dc21663260332a6dd78a98022169","source":{"kind":"arxiv","id":"2408.12466","version":1},"attestation_state":"computed","paper":{"title":"WCEbleedGen: A wireless capsule endoscopy dataset and its benchmarking for automatic bleeding classification, detection, and segmentation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Amirreza Mahbod, Deepak Gunjan, Florian Schwarzhans, Manas Dhir, Nidhi Goel, Palak Handa, Ramona Woitek","submitted_at":"2024-08-22T15:06:50Z","abstract_excerpt":"Computer-based analysis of Wireless Capsule Endoscopy (WCE) is crucial. However, a medically annotated WCE dataset for training and evaluation of automatic classification, detection, and segmentation of bleeding and non-bleeding frames is currently lacking. The present work focused on development of a medically annotated WCE dataset called WCEbleedGen for automatic classification, detection, and segmentation of bleeding and non-bleeding frames. It comprises 2,618 WCE bleeding and non-bleeding frames which were collected from various internet resources and existing WCE datasets. A comprehensive"},"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":"2408.12466","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-22T15:06:50Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"8732d3a124445354f5371f99941a838d8e615b04a97a6a904db712af46c2faa6","abstract_canon_sha256":"4b977588205e4b9de0fd76deaf7107b6240260dae73bbf0c4d0043aa6db33866"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:58:10.471277Z","signature_b64":"oVwQPcyGZC19IPGkMznfEBIAP3sW3s/wnnyBEvJMIEC5B4MMpp/QbG1r4fYoXqk+fBe8QoOIZda9iPqS2ukbAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a7cf635aaf4d5a419045c7a7f4d98fc71e8dc21663260332a6dd78a98022169","last_reissued_at":"2026-07-05T08:58:10.470770Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:58:10.470770Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"WCEbleedGen: A wireless capsule endoscopy dataset and its benchmarking for automatic bleeding classification, detection, and segmentation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Amirreza Mahbod, Deepak Gunjan, Florian Schwarzhans, Manas Dhir, Nidhi Goel, Palak Handa, Ramona Woitek","submitted_at":"2024-08-22T15:06:50Z","abstract_excerpt":"Computer-based analysis of Wireless Capsule Endoscopy (WCE) is crucial. However, a medically annotated WCE dataset for training and evaluation of automatic classification, detection, and segmentation of bleeding and non-bleeding frames is currently lacking. The present work focused on development of a medically annotated WCE dataset called WCEbleedGen for automatic classification, detection, and segmentation of bleeding and non-bleeding frames. It comprises 2,618 WCE bleeding and non-bleeding frames which were collected from various internet resources and existing WCE datasets. A comprehensive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.12466","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/2408.12466/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":"2408.12466","created_at":"2026-07-05T08:58:10.470831+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.12466v1","created_at":"2026-07-05T08:58:10.470831+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.12466","created_at":"2026-07-05T08:58:10.470831+00:00"},{"alias_kind":"pith_short_12","alias_value":"HJ6PMNNK6TK2","created_at":"2026-07-05T08:58:10.470831+00:00"},{"alias_kind":"pith_short_16","alias_value":"HJ6PMNNK6TK2IGIE","created_at":"2026-07-05T08:58:10.470831+00:00"},{"alias_kind":"pith_short_8","alias_value":"HJ6PMNNK","created_at":"2026-07-05T08:58:10.470831+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.15094","citing_title":"BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking","ref_index":21,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R","json":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R.json","graph_json":"https://pith.science/api/pith-number/HJ6PMNNK6TK2IGIELR5H6TMY7R/graph.json","events_json":"https://pith.science/api/pith-number/HJ6PMNNK6TK2IGIELR5H6TMY7R/events.json","paper":"https://pith.science/paper/HJ6PMNNK"},"agent_actions":{"view_html":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R","download_json":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R.json","view_paper":"https://pith.science/paper/HJ6PMNNK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.12466&json=true","fetch_graph":"https://pith.science/api/pith-number/HJ6PMNNK6TK2IGIELR5H6TMY7R/graph.json","fetch_events":"https://pith.science/api/pith-number/HJ6PMNNK6TK2IGIELR5H6TMY7R/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R/action/storage_attestation","attest_author":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R/action/author_attestation","sign_citation":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R/action/citation_signature","submit_replication":"https://pith.science/pith/HJ6PMNNK6TK2IGIELR5H6TMY7R/action/replication_record"}},"created_at":"2026-07-05T08:58:10.470831+00:00","updated_at":"2026-07-05T08:58:10.470831+00:00"}