{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:67TLGBDBGOFE27HITWXHLST4SX","short_pith_number":"pith:67TLGBDB","schema_version":"1.0","canonical_sha256":"f7e6b30461338a4d7ce89dae75ca7c95e0bf9ca61c1736ade5936fe7f7976e76","source":{"kind":"arxiv","id":"2206.06665","version":3},"attestation_state":"computed","paper":{"title":"Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Tianqi Xiang, Xiaomeng Li, Yiduo Yu, Yi Li, Yiwen Zou","submitted_at":"2022-06-14T07:53:03Z","abstract_excerpt":"Developing an AI-assisted gland segmentation method from histology images is critical for automatic cancer diagnosis and prognosis; however, the high cost of pixel-level annotations hinders its applications to broader diseases. Existing weakly-supervised semantic segmentation methods in computer vision achieve degenerative results for gland segmentation, since the characteristics and problems of glandular datasets are different from general object datasets. We observe that, unlike natural images, the key problem with histology images is the confusion of classes owning to morphological homogene"},"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":"2206.06665","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-14T07:53:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8841255f2c62e919794ef0e6c511ca9077dab3be987602ab77ae34c9e51f7245","abstract_canon_sha256":"f7883a6176c7f8fa52e70471456914be1afc3151e7ca65e6ca934752531f55cb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:34:54.302514Z","signature_b64":"oKfrDEdUwQ6oC4lGAuXi5K45PG+4gRYrabvcxFRK5zP6A8lR2WtIJ+RkdVUNh0sbCW/np2PhJ2/c0WipUG84CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7e6b30461338a4d7ce89dae75ca7c95e0bf9ca61c1736ade5936fe7f7976e76","last_reissued_at":"2026-07-05T04:34:54.302121Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:34:54.302121Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Tianqi Xiang, Xiaomeng Li, Yiduo Yu, Yi Li, Yiwen Zou","submitted_at":"2022-06-14T07:53:03Z","abstract_excerpt":"Developing an AI-assisted gland segmentation method from histology images is critical for automatic cancer diagnosis and prognosis; however, the high cost of pixel-level annotations hinders its applications to broader diseases. Existing weakly-supervised semantic segmentation methods in computer vision achieve degenerative results for gland segmentation, since the characteristics and problems of glandular datasets are different from general object datasets. We observe that, unlike natural images, the key problem with histology images is the confusion of classes owning to morphological homogene"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.06665","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/2206.06665/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":"2206.06665","created_at":"2026-07-05T04:34:54.302187+00:00"},{"alias_kind":"arxiv_version","alias_value":"2206.06665v3","created_at":"2026-07-05T04:34:54.302187+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.06665","created_at":"2026-07-05T04:34:54.302187+00:00"},{"alias_kind":"pith_short_12","alias_value":"67TLGBDBGOFE","created_at":"2026-07-05T04:34:54.302187+00:00"},{"alias_kind":"pith_short_16","alias_value":"67TLGBDBGOFE27HI","created_at":"2026-07-05T04:34:54.302187+00:00"},{"alias_kind":"pith_short_8","alias_value":"67TLGBDB","created_at":"2026-07-05T04:34:54.302187+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX","json":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX.json","graph_json":"https://pith.science/api/pith-number/67TLGBDBGOFE27HITWXHLST4SX/graph.json","events_json":"https://pith.science/api/pith-number/67TLGBDBGOFE27HITWXHLST4SX/events.json","paper":"https://pith.science/paper/67TLGBDB"},"agent_actions":{"view_html":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX","download_json":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX.json","view_paper":"https://pith.science/paper/67TLGBDB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2206.06665&json=true","fetch_graph":"https://pith.science/api/pith-number/67TLGBDBGOFE27HITWXHLST4SX/graph.json","fetch_events":"https://pith.science/api/pith-number/67TLGBDBGOFE27HITWXHLST4SX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX/action/storage_attestation","attest_author":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX/action/author_attestation","sign_citation":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX/action/citation_signature","submit_replication":"https://pith.science/pith/67TLGBDBGOFE27HITWXHLST4SX/action/replication_record"}},"created_at":"2026-07-05T04:34:54.302187+00:00","updated_at":"2026-07-05T04:34:54.302187+00:00"}