{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:P3UMHNKWKH3Y2Q6C344XGP22GX","short_pith_number":"pith:P3UMHNKW","canonical_record":{"source":{"id":"2211.13440","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-11-24T06:57:16Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3f336bf313bd8e105531293430861eb5a2ce3bcf0f211bc8347acd26da244f80","abstract_canon_sha256":"34f53f9b228e08ecb5806ac73cc674c22bf7606e4d83b15b74f47900ca060b74"},"schema_version":"1.0"},"canonical_sha256":"7ee8c3b55651f78d43c2df39733f5a35f7be01d067440a3dd7624b22fd9ba524","source":{"kind":"arxiv","id":"2211.13440","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.13440","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"arxiv_version","alias_value":"2211.13440v1","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.13440","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_12","alias_value":"P3UMHNKWKH3Y","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_16","alias_value":"P3UMHNKWKH3Y2Q6C","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_8","alias_value":"P3UMHNKW","created_at":"2026-07-05T05:19:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:P3UMHNKWKH3Y2Q6C344XGP22GX","target":"record","payload":{"canonical_record":{"source":{"id":"2211.13440","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-11-24T06:57:16Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3f336bf313bd8e105531293430861eb5a2ce3bcf0f211bc8347acd26da244f80","abstract_canon_sha256":"34f53f9b228e08ecb5806ac73cc674c22bf7606e4d83b15b74f47900ca060b74"},"schema_version":"1.0"},"canonical_sha256":"7ee8c3b55651f78d43c2df39733f5a35f7be01d067440a3dd7624b22fd9ba524","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:19:22.210812Z","signature_b64":"DkFoUpqWDMr3s4nOKvVTTdKvNQCqY2PehPnALSvh3AOfmO9PetxyzSp3GoKe5br9QqMxPX4scGnGZ3VUpo24BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ee8c3b55651f78d43c2df39733f5a35f7be01d067440a3dd7624b22fd9ba524","last_reissued_at":"2026-07-05T05:19:22.210329Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:19:22.210329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.13440","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":"2026-07-05T05:19:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ufh7caU7mGXoYVpEYTmWBAC8WMCz0u3VNlvT4zrISHNu5GuAuHgxjFsih/dpivF+8IgLhdvsfCUkWwHCCEkVAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:03.310731Z"},"content_sha256":"c62d2cd7522f3b5a9f7bd3a7e0e6e727bf357ce291e12a0adcb553a392fad34e","schema_version":"1.0","event_id":"sha256:c62d2cd7522f3b5a9f7bd3a7e0e6e727bf357ce291e12a0adcb553a392fad34e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:P3UMHNKWKH3Y2Q6C344XGP22GX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Iterative Data Refinement for Self-Supervised MR Image Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Cheng Li, Hairong Zheng, Juan Zou, Shanshan Wang, Xiawu Zheng, Xue Liu","submitted_at":"2022-11-24T06:57:16Z","abstract_excerpt":"Magnetic Resonance Imaging (MRI) has become an important technique in the clinic for the visualization, detection, and diagnosis of various diseases. However, one bottleneck limitation of MRI is the relatively slow data acquisition process. Fast MRI based on k-space undersampling and high-quality image reconstruction has been widely utilized, and many deep learning-based methods have been developed in recent years. Although promising results have been achieved, most existing methods require fully-sampled reference data for training the deep learning models. Unfortunately, fully-sampled MRI dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.13440","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/2211.13440/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":"2026-07-05T05:19:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pNvnIqTipJ0d2p9nSDWpO+xisWKnyLhPa9rSs6TuccfXppotxC3vjtW1SDOgOPb4I8aWxFl4BQci7a2LuHRpCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:03.311253Z"},"content_sha256":"3c24b05e351ea648d5c06eca4f05f7f26e636abc984242ae3bfa1cffce5d98e6","schema_version":"1.0","event_id":"sha256:3c24b05e351ea648d5c06eca4f05f7f26e636abc984242ae3bfa1cffce5d98e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/bundle.json","state_url":"https://pith.science/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/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":"2026-08-05T02:31:03Z","links":{"resolver":"https://pith.science/pith/P3UMHNKWKH3Y2Q6C344XGP22GX","bundle":"https://pith.science/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/bundle.json","state":"https://pith.science/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P3UMHNKWKH3Y2Q6C344XGP22GX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:P3UMHNKWKH3Y2Q6C344XGP22GX","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":"34f53f9b228e08ecb5806ac73cc674c22bf7606e4d83b15b74f47900ca060b74","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-11-24T06:57:16Z","title_canon_sha256":"3f336bf313bd8e105531293430861eb5a2ce3bcf0f211bc8347acd26da244f80"},"schema_version":"1.0","source":{"id":"2211.13440","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.13440","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"arxiv_version","alias_value":"2211.13440v1","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.13440","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_12","alias_value":"P3UMHNKWKH3Y","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_16","alias_value":"P3UMHNKWKH3Y2Q6C","created_at":"2026-07-05T05:19:22Z"},{"alias_kind":"pith_short_8","alias_value":"P3UMHNKW","created_at":"2026-07-05T05:19:22Z"}],"graph_snapshots":[{"event_id":"sha256:3c24b05e351ea648d5c06eca4f05f7f26e636abc984242ae3bfa1cffce5d98e6","target":"graph","created_at":"2026-07-05T05:19:22Z","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/2211.13440/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Magnetic Resonance Imaging (MRI) has become an important technique in the clinic for the visualization, detection, and diagnosis of various diseases. However, one bottleneck limitation of MRI is the relatively slow data acquisition process. Fast MRI based on k-space undersampling and high-quality image reconstruction has been widely utilized, and many deep learning-based methods have been developed in recent years. Although promising results have been achieved, most existing methods require fully-sampled reference data for training the deep learning models. Unfortunately, fully-sampled MRI dat","authors_text":"Cheng Li, Hairong Zheng, Juan Zou, Shanshan Wang, Xiawu Zheng, Xue Liu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-11-24T06:57:16Z","title":"Iterative Data Refinement for Self-Supervised MR Image Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.13440","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:c62d2cd7522f3b5a9f7bd3a7e0e6e727bf357ce291e12a0adcb553a392fad34e","target":"record","created_at":"2026-07-05T05:19:22Z","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":"34f53f9b228e08ecb5806ac73cc674c22bf7606e4d83b15b74f47900ca060b74","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-11-24T06:57:16Z","title_canon_sha256":"3f336bf313bd8e105531293430861eb5a2ce3bcf0f211bc8347acd26da244f80"},"schema_version":"1.0","source":{"id":"2211.13440","kind":"arxiv","version":1}},"canonical_sha256":"7ee8c3b55651f78d43c2df39733f5a35f7be01d067440a3dd7624b22fd9ba524","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ee8c3b55651f78d43c2df39733f5a35f7be01d067440a3dd7624b22fd9ba524","first_computed_at":"2026-07-05T05:19:22.210329Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:19:22.210329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DkFoUpqWDMr3s4nOKvVTTdKvNQCqY2PehPnALSvh3AOfmO9PetxyzSp3GoKe5br9QqMxPX4scGnGZ3VUpo24BA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:19:22.210812Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.13440","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c62d2cd7522f3b5a9f7bd3a7e0e6e727bf357ce291e12a0adcb553a392fad34e","sha256:3c24b05e351ea648d5c06eca4f05f7f26e636abc984242ae3bfa1cffce5d98e6"],"state_sha256":"dbf31789d3cdb6157a7d10224d3a3e316886a5e8fe3a1fd0713e9b991d180606"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tir3Yu7I2winkTj5D+PaN8tzr944rZjx9TnNyuukY/2l2o9XSZjfoJt+k8Fs0ITLT7Mn+PvV9UQkUmYNtXCpCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:31:03.315128Z","bundle_sha256":"7c77ffcf64411a750b57e09bfb39cd44c979fccce3980e3bf57f0afc2b581970"}}