{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:5DXBNS4KD7KRSDK2MDTCUV4CN6","short_pith_number":"pith:5DXBNS4K","canonical_record":{"source":{"id":"2203.04306","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T12:35:07Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"dc4f621333d504a572feadb0ada79cf28e699562b5f711ea970941ef4f2eff18","abstract_canon_sha256":"27599a8524f1d3b4754a65489975979fd4fd62816231e34bb075781e7907117d"},"schema_version":"1.0"},"canonical_sha256":"e8ee16cb8a1fd5190d5a60e62a57826f9abffe7edde931efda368ae20f883dfd","source":{"kind":"arxiv","id":"2203.04306","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04306","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04306v2","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04306","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_12","alias_value":"5DXBNS4KD7KR","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_16","alias_value":"5DXBNS4KD7KRSDK2","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_8","alias_value":"5DXBNS4K","created_at":"2026-07-05T05:03:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:5DXBNS4KD7KRSDK2MDTCUV4CN6","target":"record","payload":{"canonical_record":{"source":{"id":"2203.04306","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T12:35:07Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"dc4f621333d504a572feadb0ada79cf28e699562b5f711ea970941ef4f2eff18","abstract_canon_sha256":"27599a8524f1d3b4754a65489975979fd4fd62816231e34bb075781e7907117d"},"schema_version":"1.0"},"canonical_sha256":"e8ee16cb8a1fd5190d5a60e62a57826f9abffe7edde931efda368ae20f883dfd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:03:36.202745Z","signature_b64":"RdjDO+Y4HuyWfIHagbT9OHSsZC8aiWjtaDSkPofRbfuViWghDf2lujtqd6kb0U/MqVjHvHcnSaX/P8hYllQpAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8ee16cb8a1fd5190d5a60e62a57826f9abffe7edde931efda368ae20f883dfd","last_reissued_at":"2026-07-05T05:03:36.202337Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:03:36.202337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.04306","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:03:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jzP+HueseXa4DmDOzGkoePagNbeLLfov5h+Ufp/2WinYpIIuIjtaH34gcp5br/VCxbjTlfa4eQnpkN2aJeuOCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:42:42.159749Z"},"content_sha256":"4b622849f0759e586933c152279311b2f1dc271cb0c78f68e962d4ec87e6780e","schema_version":"1.0","event_id":"sha256:4b622849f0759e586933c152279311b2f1dc271cb0c78f68e962d4ec87e6780e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:5DXBNS4KD7KRSDK2MDTCUV4CN6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion Models for Medical Anomaly Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Florentin Bieder, Julia Wolleb, Philippe C. Cattin, Robin Sandk\\\"uhler","submitted_at":"2022-03-08T12:35:07Z","abstract_excerpt":"In medical applications, weakly supervised anomaly detection methods are of great interest, as only image-level annotations are required for training. Current anomaly detection methods mainly rely on generative adversarial networks or autoencoder models. Those models are often complicated to train or have difficulties to preserve fine details in the image. We present a novel weakly supervised anomaly detection method based on denoising diffusion implicit models. We combine the deterministic iterative noising and denoising scheme with classifier guidance for image-to-image translation between d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04306","kind":"arxiv","version":2},"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/2203.04306/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":"2026-07-05T05:03:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k2eSiov4pJr8P+dM9GI3XQs5j9HD366NQ13lucZVBoo20AdiIhuCfhuMSMmZvr9KeJoGyUJwgGPkdMQuzMyvCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:42:42.160134Z"},"content_sha256":"5e057ae87a19d0665ee546636149535dc6f1e2c9dcd7ab474da33dece920c293","schema_version":"1.0","event_id":"sha256:5e057ae87a19d0665ee546636149535dc6f1e2c9dcd7ab474da33dece920c293"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/bundle.json","state_url":"https://pith.science/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/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":"2026-08-12T22:42:42Z","links":{"resolver":"https://pith.science/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6","bundle":"https://pith.science/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/bundle.json","state":"https://pith.science/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5DXBNS4KD7KRSDK2MDTCUV4CN6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5DXBNS4KD7KRSDK2MDTCUV4CN6","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":"27599a8524f1d3b4754a65489975979fd4fd62816231e34bb075781e7907117d","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T12:35:07Z","title_canon_sha256":"dc4f621333d504a572feadb0ada79cf28e699562b5f711ea970941ef4f2eff18"},"schema_version":"1.0","source":{"id":"2203.04306","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04306","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04306v2","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04306","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_12","alias_value":"5DXBNS4KD7KR","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_16","alias_value":"5DXBNS4KD7KRSDK2","created_at":"2026-07-05T05:03:36Z"},{"alias_kind":"pith_short_8","alias_value":"5DXBNS4K","created_at":"2026-07-05T05:03:36Z"}],"graph_snapshots":[{"event_id":"sha256:5e057ae87a19d0665ee546636149535dc6f1e2c9dcd7ab474da33dece920c293","target":"graph","created_at":"2026-07-05T05:03:36Z","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/2203.04306/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In medical applications, weakly supervised anomaly detection methods are of great interest, as only image-level annotations are required for training. Current anomaly detection methods mainly rely on generative adversarial networks or autoencoder models. Those models are often complicated to train or have difficulties to preserve fine details in the image. We present a novel weakly supervised anomaly detection method based on denoising diffusion implicit models. We combine the deterministic iterative noising and denoising scheme with classifier guidance for image-to-image translation between d","authors_text":"Florentin Bieder, Julia Wolleb, Philippe C. Cattin, Robin Sandk\\\"uhler","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T12:35:07Z","title":"Diffusion Models for Medical Anomaly Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04306","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":"sha256:4b622849f0759e586933c152279311b2f1dc271cb0c78f68e962d4ec87e6780e","target":"record","created_at":"2026-07-05T05:03:36Z","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":"27599a8524f1d3b4754a65489975979fd4fd62816231e34bb075781e7907117d","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-03-08T12:35:07Z","title_canon_sha256":"dc4f621333d504a572feadb0ada79cf28e699562b5f711ea970941ef4f2eff18"},"schema_version":"1.0","source":{"id":"2203.04306","kind":"arxiv","version":2}},"canonical_sha256":"e8ee16cb8a1fd5190d5a60e62a57826f9abffe7edde931efda368ae20f883dfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e8ee16cb8a1fd5190d5a60e62a57826f9abffe7edde931efda368ae20f883dfd","first_computed_at":"2026-07-05T05:03:36.202337Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:03:36.202337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RdjDO+Y4HuyWfIHagbT9OHSsZC8aiWjtaDSkPofRbfuViWghDf2lujtqd6kb0U/MqVjHvHcnSaX/P8hYllQpAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:03:36.202745Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.04306","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b622849f0759e586933c152279311b2f1dc271cb0c78f68e962d4ec87e6780e","sha256:5e057ae87a19d0665ee546636149535dc6f1e2c9dcd7ab474da33dece920c293"],"state_sha256":"da4bb9edaf315168a8e9cdcefc4410a851560a35404e6333ca04fd3a3c945712"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"54MX5gRSlkinEwlTYeFZg1tI/nmmSlrcC2ViuMsqehz6hGBPyCOYO2/UDWBq9K8eu2AgXU4PcD75c2Gdi3pDBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T22:42:42.163071Z","bundle_sha256":"432a660509256a62b33cdef1c1d5c4bc1f2e8b15abd96256e30cb91ffb242a84"}}