{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:BD6VAFQQF5EXMQBJ43Q2SDTEJO","short_pith_number":"pith:BD6VAFQQ","canonical_record":{"source":{"id":"1810.01967","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-03T20:52:49Z","cross_cats_sorted":[],"title_canon_sha256":"3eb427603bf0fc432fc2b35ca88191d0c6f6f7b1d49ab774e9310276de8a7c41","abstract_canon_sha256":"b21c7dfae94bd980a1b8c240dece33f59f627db44952a061fdd7125c1221dd91"},"schema_version":"1.0"},"canonical_sha256":"08fd5016102f49764029e6e1a90e644bac92faa365ee3bc28273007aea777808","source":{"kind":"arxiv","id":"1810.01967","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01967","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01967v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01967","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"BD6VAFQQF5EX","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"BD6VAFQQF5EXMQBJ","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"BD6VAFQQ","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:BD6VAFQQF5EXMQBJ43Q2SDTEJO","target":"record","payload":{"canonical_record":{"source":{"id":"1810.01967","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-03T20:52:49Z","cross_cats_sorted":[],"title_canon_sha256":"3eb427603bf0fc432fc2b35ca88191d0c6f6f7b1d49ab774e9310276de8a7c41","abstract_canon_sha256":"b21c7dfae94bd980a1b8c240dece33f59f627db44952a061fdd7125c1221dd91"},"schema_version":"1.0"},"canonical_sha256":"08fd5016102f49764029e6e1a90e644bac92faa365ee3bc28273007aea777808","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:06.749067Z","signature_b64":"enZS7lHpWQ6BhVi4vnV6NQrlYGFTnGgyg8NYNoo6xkTiqhXwbB2UADTqu0stbG234H/Sl5Yb2uHkdoKhWY9nBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08fd5016102f49764029e6e1a90e644bac92faa365ee3bc28273007aea777808","last_reissued_at":"2026-05-18T00:04:06.748489Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:06.748489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.01967","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":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fek6Jtw3+NiMJyufGzk4rqU1nhTtqVHWktdJX0jay+Cp81DYqWDKWqoHB2bCReycDQ42J6TAqJ9qonSuzkQfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T23:11:11.579504Z"},"content_sha256":"1174f6200958d7f5727c405e6289f596644dae0532f3345d143815441cf1527e","schema_version":"1.0","event_id":"sha256:1174f6200958d7f5727c405e6289f596644dae0532f3345d143815441cf1527e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:BD6VAFQQF5EXMQBJ43Q2SDTEJO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mike Davies, Mohammad Golbabaee, Yves Wiaux, Zhouye Chen","submitted_at":"2018-10-03T20:52:49Z","abstract_excerpt":"Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in multi-parametric quantitative MRI applications. We address this shortcoming by arranging dictionary atoms in the form of cover tree structures and adopt the corresponding fast approximate nearest neighbour searches to accelerate matched-filtering. For datasets belonging to smooth low-dimensional manifolds cover trees offer search complexities logarithmic in terms of data populat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01967","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":""},"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":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/cykHDGcZI6lJ8Tjj+iZOxfvYwYS4PwrHRw9mHA9v1AmN2HgWMqSMB76Z4t5ySzhO0uJFFMLAu/oR80UFSE+Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T23:11:11.579841Z"},"content_sha256":"ea9c3b1646a1b90a8a5b26a2b524baa90042367046869ce43adf79fc6a527903","schema_version":"1.0","event_id":"sha256:ea9c3b1646a1b90a8a5b26a2b524baa90042367046869ce43adf79fc6a527903"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/bundle.json","state_url":"https://pith.science/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/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":"2026-06-08T23:11:11Z","links":{"resolver":"https://pith.science/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO","bundle":"https://pith.science/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/bundle.json","state":"https://pith.science/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BD6VAFQQF5EXMQBJ43Q2SDTEJO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:BD6VAFQQF5EXMQBJ43Q2SDTEJO","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":"b21c7dfae94bd980a1b8c240dece33f59f627db44952a061fdd7125c1221dd91","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-03T20:52:49Z","title_canon_sha256":"3eb427603bf0fc432fc2b35ca88191d0c6f6f7b1d49ab774e9310276de8a7c41"},"schema_version":"1.0","source":{"id":"1810.01967","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01967","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01967v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01967","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"BD6VAFQQF5EX","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"BD6VAFQQF5EXMQBJ","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"BD6VAFQQ","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:ea9c3b1646a1b90a8a5b26a2b524baa90042367046869ce43adf79fc6a527903","target":"graph","created_at":"2026-05-18T00:04:06Z","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"},"paper":{"abstract_excerpt":"Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in multi-parametric quantitative MRI applications. We address this shortcoming by arranging dictionary atoms in the form of cover tree structures and adopt the corresponding fast approximate nearest neighbour searches to accelerate matched-filtering. For datasets belonging to smooth low-dimensional manifolds cover trees offer search complexities logarithmic in terms of data populat","authors_text":"Mike Davies, Mohammad Golbabaee, Yves Wiaux, Zhouye Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-03T20:52:49Z","title":"CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01967","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":"sha256:1174f6200958d7f5727c405e6289f596644dae0532f3345d143815441cf1527e","target":"record","created_at":"2026-05-18T00:04:06Z","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":"b21c7dfae94bd980a1b8c240dece33f59f627db44952a061fdd7125c1221dd91","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-03T20:52:49Z","title_canon_sha256":"3eb427603bf0fc432fc2b35ca88191d0c6f6f7b1d49ab774e9310276de8a7c41"},"schema_version":"1.0","source":{"id":"1810.01967","kind":"arxiv","version":1}},"canonical_sha256":"08fd5016102f49764029e6e1a90e644bac92faa365ee3bc28273007aea777808","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08fd5016102f49764029e6e1a90e644bac92faa365ee3bc28273007aea777808","first_computed_at":"2026-05-18T00:04:06.748489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:06.748489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"enZS7lHpWQ6BhVi4vnV6NQrlYGFTnGgyg8NYNoo6xkTiqhXwbB2UADTqu0stbG234H/Sl5Yb2uHkdoKhWY9nBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:06.749067Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.01967","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1174f6200958d7f5727c405e6289f596644dae0532f3345d143815441cf1527e","sha256:ea9c3b1646a1b90a8a5b26a2b524baa90042367046869ce43adf79fc6a527903"],"state_sha256":"2fb2df6d57f7a15ea2fe2343779ea18b0e5949906d31129f6a9b2048aa7b291f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KBX5+ehJFyGWlaZzAWmA05WxiFSdgrgRj2BIm1bU9h7TWGfFnCkZOzD/Z36XAgUCb+abrUcZ5KpqGCo1uiFrBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T23:11:11.581578Z","bundle_sha256":"b926fdb74657edd0724aaf33e04c0630183baad87373536258a8c6442ff5c17e"}}