{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:C7EKP2DUQ2LGCOJPJ7MGCZSEMD","short_pith_number":"pith:C7EKP2DU","canonical_record":{"source":{"id":"2501.17906","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-29T14:32:22Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"e24463fc2956e02c52b67cf6ab2927013790caab5bbf2ca67b097ac075b70425","abstract_canon_sha256":"c89b2dba9081646db201eb4c458bd6f6cef8914c09f6b18e46be133df7e19d70"},"schema_version":"1.0"},"canonical_sha256":"17c8a7e874869661392f4fd861664460edc8e1bc41880734380bf21de1b6466b","source":{"kind":"arxiv","id":"2501.17906","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.17906","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"arxiv_version","alias_value":"2501.17906v1","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.17906","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_12","alias_value":"C7EKP2DUQ2LG","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_16","alias_value":"C7EKP2DUQ2LGCOJP","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_8","alias_value":"C7EKP2DU","created_at":"2026-07-05T10:07:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:C7EKP2DUQ2LGCOJPJ7MGCZSEMD","target":"record","payload":{"canonical_record":{"source":{"id":"2501.17906","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-29T14:32:22Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"e24463fc2956e02c52b67cf6ab2927013790caab5bbf2ca67b097ac075b70425","abstract_canon_sha256":"c89b2dba9081646db201eb4c458bd6f6cef8914c09f6b18e46be133df7e19d70"},"schema_version":"1.0"},"canonical_sha256":"17c8a7e874869661392f4fd861664460edc8e1bc41880734380bf21de1b6466b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:04.075438Z","signature_b64":"KUQW1Ri5y28diuLt8poQ+pAjGPdZBXoKlMUR6lqqNYBuxHpOmEhiqVxJ+h3NILbXSaWPpCehZWv3pz/gkJLIBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17c8a7e874869661392f4fd861664460edc8e1bc41880734380bf21de1b6466b","last_reissued_at":"2026-07-05T10:07:04.075016Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:04.075016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.17906","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:07:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ts6tyVa8xdUzOqtBYf/8epqb1sfM8ShtbVr1Tt8S5NeIfqUASb0GH2f3JInE+GpigQBizxINwXh1ySzM4AgyDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:20:34.512840Z"},"content_sha256":"0f397b13c3122abdb7c96f49a6a175d245b7f62d844d5410923019fe2db697ed","schema_version":"1.0","event_id":"sha256:0f397b13c3122abdb7c96f49a6a175d245b7f62d844d5410923019fe2db697ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:C7EKP2DUQ2LGCOJPJ7MGCZSEMD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Patch-GAN with Targeted Patch Ranking for Fine-Grained Novelty Detection in Medical Imaging","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Guang Yang, Jianguo Zhang, Jingchao Peng, Jingkun Chen, Jungong Han, Tianlu Zhang, Vicente Grau, Xiao Zhang","submitted_at":"2025-01-29T14:32:22Z","abstract_excerpt":"Detecting novel anomalies in medical imaging is challenging due to the limited availability of labeled data for rare abnormalities, which often display high variability and subtlety. This challenge is further compounded when small abnormal regions are embedded within larger normal areas, as whole-image predictions frequently overlook these subtle deviations. To address these issues, we propose an unsupervised Patch-GAN framework designed to detect and localize anomalies by capturing both local detail and global structure. Our framework first reconstructs masked images to learn fine-grained, no"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.17906","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/2501.17906/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":"2026-07-05T10:07:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0DS4DlXviLEC7uiMJenmKRUtAt1xUJX8mZjQs4lbpGaOdFmHcx9eYmEZpgA2QMeuLUCzSJAF6ZSsqoqc7cPbBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T19:20:34.513335Z"},"content_sha256":"cb677fbed21eec5d9c4ccec171aa396e37b6b012a317a091feeb51e52b37a5bb","schema_version":"1.0","event_id":"sha256:cb677fbed21eec5d9c4ccec171aa396e37b6b012a317a091feeb51e52b37a5bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/bundle.json","state_url":"https://pith.science/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/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":"2026-08-03T19:20:34Z","links":{"resolver":"https://pith.science/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD","bundle":"https://pith.science/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/bundle.json","state":"https://pith.science/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C7EKP2DUQ2LGCOJPJ7MGCZSEMD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:C7EKP2DUQ2LGCOJPJ7MGCZSEMD","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":"c89b2dba9081646db201eb4c458bd6f6cef8914c09f6b18e46be133df7e19d70","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-29T14:32:22Z","title_canon_sha256":"e24463fc2956e02c52b67cf6ab2927013790caab5bbf2ca67b097ac075b70425"},"schema_version":"1.0","source":{"id":"2501.17906","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.17906","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"arxiv_version","alias_value":"2501.17906v1","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.17906","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_12","alias_value":"C7EKP2DUQ2LG","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_16","alias_value":"C7EKP2DUQ2LGCOJP","created_at":"2026-07-05T10:07:04Z"},{"alias_kind":"pith_short_8","alias_value":"C7EKP2DU","created_at":"2026-07-05T10:07:04Z"}],"graph_snapshots":[{"event_id":"sha256:cb677fbed21eec5d9c4ccec171aa396e37b6b012a317a091feeb51e52b37a5bb","target":"graph","created_at":"2026-07-05T10:07:04Z","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/2501.17906/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Detecting novel anomalies in medical imaging is challenging due to the limited availability of labeled data for rare abnormalities, which often display high variability and subtlety. This challenge is further compounded when small abnormal regions are embedded within larger normal areas, as whole-image predictions frequently overlook these subtle deviations. To address these issues, we propose an unsupervised Patch-GAN framework designed to detect and localize anomalies by capturing both local detail and global structure. Our framework first reconstructs masked images to learn fine-grained, no","authors_text":"Guang Yang, Jianguo Zhang, Jingchao Peng, Jingkun Chen, Jungong Han, Tianlu Zhang, Vicente Grau, Xiao Zhang","cross_cats":["eess.IV"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-29T14:32:22Z","title":"Unsupervised Patch-GAN with Targeted Patch Ranking for Fine-Grained Novelty Detection in Medical Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.17906","kind":"arxiv","version":1},"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":"sha256:0f397b13c3122abdb7c96f49a6a175d245b7f62d844d5410923019fe2db697ed","target":"record","created_at":"2026-07-05T10:07:04Z","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":"c89b2dba9081646db201eb4c458bd6f6cef8914c09f6b18e46be133df7e19d70","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-29T14:32:22Z","title_canon_sha256":"e24463fc2956e02c52b67cf6ab2927013790caab5bbf2ca67b097ac075b70425"},"schema_version":"1.0","source":{"id":"2501.17906","kind":"arxiv","version":1}},"canonical_sha256":"17c8a7e874869661392f4fd861664460edc8e1bc41880734380bf21de1b6466b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17c8a7e874869661392f4fd861664460edc8e1bc41880734380bf21de1b6466b","first_computed_at":"2026-07-05T10:07:04.075016Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:04.075016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KUQW1Ri5y28diuLt8poQ+pAjGPdZBXoKlMUR6lqqNYBuxHpOmEhiqVxJ+h3NILbXSaWPpCehZWv3pz/gkJLIBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:04.075438Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.17906","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f397b13c3122abdb7c96f49a6a175d245b7f62d844d5410923019fe2db697ed","sha256:cb677fbed21eec5d9c4ccec171aa396e37b6b012a317a091feeb51e52b37a5bb"],"state_sha256":"55436f6a224bab5112edab40266a981e1c3097677a437c2ade7c626522c664ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T3oSn93s5KvcwC6NaQNF7yR6ZCzKpk6J9Zvuis+bwwTcfa3lx72S8tlienOq9x5qxC7jKMSN6Ego0kZxHyXOBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T19:20:34.517457Z","bundle_sha256":"13834895809893308668d36eb398ed2c6ae19cfe8ca1971f6161c84f7c4f17ca"}}