{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:NTSAIRKT65UDL53ND4HTHQERB7","short_pith_number":"pith:NTSAIRKT","canonical_record":{"source":{"id":"2309.14392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-09-25T11:07:25Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"fbe8f5e1f36a946a3b78839fe8883a53e1e8b46f638b3ddbb3c66bcea5acc6f0","abstract_canon_sha256":"d5ce5378c83a8843a97800f08286b7dafed5a13a9ba2ad138b813a22ea816368"},"schema_version":"1.0"},"canonical_sha256":"6ce4044553f76835f76d1f0f33c0910fd75d9930d458a30e9d39202ac0864046","source":{"kind":"arxiv","id":"2309.14392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.14392","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"arxiv_version","alias_value":"2309.14392v1","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.14392","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_12","alias_value":"NTSAIRKT65UD","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_16","alias_value":"NTSAIRKT65UDL53N","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_8","alias_value":"NTSAIRKT","created_at":"2026-07-05T06:54:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:NTSAIRKT65UDL53ND4HTHQERB7","target":"record","payload":{"canonical_record":{"source":{"id":"2309.14392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-09-25T11:07:25Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"fbe8f5e1f36a946a3b78839fe8883a53e1e8b46f638b3ddbb3c66bcea5acc6f0","abstract_canon_sha256":"d5ce5378c83a8843a97800f08286b7dafed5a13a9ba2ad138b813a22ea816368"},"schema_version":"1.0"},"canonical_sha256":"6ce4044553f76835f76d1f0f33c0910fd75d9930d458a30e9d39202ac0864046","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:54:25.028326Z","signature_b64":"FNJ/HfUf6IwssL5DEH8X8jtr6VIUABTsLCoJp6JucOzr5oBAad1s0Rq0OK+TG0jcJTkebplVO/MsQAcgF+eWBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ce4044553f76835f76d1f0f33c0910fd75d9930d458a30e9d39202ac0864046","last_reissued_at":"2026-07-05T06:54:25.027846Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:54:25.027846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.14392","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":"2026-07-05T06:54:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eg0/W09n1c3Ywjg8SX64weCBTe28dsI+2jagPftVVYnxncV8DUyv9PblEnJUI5cbBsizB05U88mne57ZO6A1DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:00:48.195941Z"},"content_sha256":"e0a2184e86053dcb6e77006d9ea6eae10e7066d61c408b41f2ff6abf13b1394e","schema_version":"1.0","event_id":"sha256:e0a2184e86053dcb6e77006d9ea6eae10e7066d61c408b41f2ff6abf13b1394e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:NTSAIRKT65UDL53ND4HTHQERB7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Rohan Dharmakumar, Sotirios A. Tsaftaris, Yuning Du, Yuyang Xue","submitted_at":"2023-09-25T11:07:25Z","abstract_excerpt":"Deep learning (DL) reconstruction particularly of MRI has led to improvements in image fidelity and reduction of acquisition time. In neuroimaging, DL methods can reconstruct high-quality images from undersampled data. However, it is essential to consider fairness in DL algorithms, particularly in terms of demographic characteristics. This study presents the first fairness analysis in a DL-based brain MRI reconstruction model. The model utilises the U-Net architecture for image reconstruction and explores the presence and sources of unfairness by implementing baseline Empirical Risk Minimisati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.14392","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/2309.14392/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":"2026-07-05T06:54:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f/Ii0HOeXkGmOxO7TrDpJavB0RqAsC21ILXu34Fk2bIoQE4p8nRU4Bf1uu/BETYarNdDHVxt5Wukxa9x0TDvAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:00:48.196328Z"},"content_sha256":"9874a69e86f1ab42e468a21500a47d8b33b906751b02ec4802c0464a7318f997","schema_version":"1.0","event_id":"sha256:9874a69e86f1ab42e468a21500a47d8b33b906751b02ec4802c0464a7318f997"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NTSAIRKT65UDL53ND4HTHQERB7/bundle.json","state_url":"https://pith.science/pith/NTSAIRKT65UDL53ND4HTHQERB7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NTSAIRKT65UDL53ND4HTHQERB7/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":"2026-07-06T17:00:48Z","links":{"resolver":"https://pith.science/pith/NTSAIRKT65UDL53ND4HTHQERB7","bundle":"https://pith.science/pith/NTSAIRKT65UDL53ND4HTHQERB7/bundle.json","state":"https://pith.science/pith/NTSAIRKT65UDL53ND4HTHQERB7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NTSAIRKT65UDL53ND4HTHQERB7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NTSAIRKT65UDL53ND4HTHQERB7","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":"d5ce5378c83a8843a97800f08286b7dafed5a13a9ba2ad138b813a22ea816368","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-09-25T11:07:25Z","title_canon_sha256":"fbe8f5e1f36a946a3b78839fe8883a53e1e8b46f638b3ddbb3c66bcea5acc6f0"},"schema_version":"1.0","source":{"id":"2309.14392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.14392","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"arxiv_version","alias_value":"2309.14392v1","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.14392","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_12","alias_value":"NTSAIRKT65UD","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_16","alias_value":"NTSAIRKT65UDL53N","created_at":"2026-07-05T06:54:25Z"},{"alias_kind":"pith_short_8","alias_value":"NTSAIRKT","created_at":"2026-07-05T06:54:25Z"}],"graph_snapshots":[{"event_id":"sha256:9874a69e86f1ab42e468a21500a47d8b33b906751b02ec4802c0464a7318f997","target":"graph","created_at":"2026-07-05T06:54:25Z","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/2309.14392/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning (DL) reconstruction particularly of MRI has led to improvements in image fidelity and reduction of acquisition time. In neuroimaging, DL methods can reconstruct high-quality images from undersampled data. However, it is essential to consider fairness in DL algorithms, particularly in terms of demographic characteristics. This study presents the first fairness analysis in a DL-based brain MRI reconstruction model. The model utilises the U-Net architecture for image reconstruction and explores the presence and sources of unfairness by implementing baseline Empirical Risk Minimisati","authors_text":"Rohan Dharmakumar, Sotirios A. Tsaftaris, Yuning Du, Yuyang Xue","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-09-25T11:07:25Z","title":"Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.14392","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:e0a2184e86053dcb6e77006d9ea6eae10e7066d61c408b41f2ff6abf13b1394e","target":"record","created_at":"2026-07-05T06:54:25Z","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":"d5ce5378c83a8843a97800f08286b7dafed5a13a9ba2ad138b813a22ea816368","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-09-25T11:07:25Z","title_canon_sha256":"fbe8f5e1f36a946a3b78839fe8883a53e1e8b46f638b3ddbb3c66bcea5acc6f0"},"schema_version":"1.0","source":{"id":"2309.14392","kind":"arxiv","version":1}},"canonical_sha256":"6ce4044553f76835f76d1f0f33c0910fd75d9930d458a30e9d39202ac0864046","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ce4044553f76835f76d1f0f33c0910fd75d9930d458a30e9d39202ac0864046","first_computed_at":"2026-07-05T06:54:25.027846Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:54:25.027846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FNJ/HfUf6IwssL5DEH8X8jtr6VIUABTsLCoJp6JucOzr5oBAad1s0Rq0OK+TG0jcJTkebplVO/MsQAcgF+eWBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:54:25.028326Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.14392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0a2184e86053dcb6e77006d9ea6eae10e7066d61c408b41f2ff6abf13b1394e","sha256:9874a69e86f1ab42e468a21500a47d8b33b906751b02ec4802c0464a7318f997"],"state_sha256":"f32430b9c4ae37f7933bd3373471f7aa46857babd8129427abd57006483d34fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NQlkNkgdrUZYxipzoWnZ06ot1B4cFWamOfV7gg4RisgmRCvA9GqxxJAVZDRX7j2950nQZqiSKKFe70sLoeL1BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:00:48.198280Z","bundle_sha256":"6fbf5bbc84ca44702bdc6d86b06bc484ec93ca1749da0e24b80fe6634728f6fe"}}