{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:B2CJXEOW4EYYLHI34APVCC5EYH","short_pith_number":"pith:B2CJXEOW","canonical_record":{"source":{"id":"2412.15740","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-12-20T10:00:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"77d1c1452fb7529c6776e5e75c598b642ae43aeef53586a80460ce23d955152c","abstract_canon_sha256":"ebaa0bd339cf11657e167795e35252d35d417e9c9c653be0da99a006dbc3c669"},"schema_version":"1.0"},"canonical_sha256":"0e849b91d6e131859d1be01f510ba4c1dec25f22214b6584b57bb9cdddfd32ba","source":{"kind":"arxiv","id":"2412.15740","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.15740","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"arxiv_version","alias_value":"2412.15740v1","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.15740","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_12","alias_value":"B2CJXEOW4EYY","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_16","alias_value":"B2CJXEOW4EYYLHI3","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_8","alias_value":"B2CJXEOW","created_at":"2026-07-05T09:52:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:B2CJXEOW4EYYLHI34APVCC5EYH","target":"record","payload":{"canonical_record":{"source":{"id":"2412.15740","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-12-20T10:00:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"77d1c1452fb7529c6776e5e75c598b642ae43aeef53586a80460ce23d955152c","abstract_canon_sha256":"ebaa0bd339cf11657e167795e35252d35d417e9c9c653be0da99a006dbc3c669"},"schema_version":"1.0"},"canonical_sha256":"0e849b91d6e131859d1be01f510ba4c1dec25f22214b6584b57bb9cdddfd32ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:52:29.252637Z","signature_b64":"i5HMekV7cR9ohGSlC4gKr/bTYsMQtvWFwsOxuFkcVGAOD3CAbr2Ww5EymJw1vpUCgz90CwIM6ov35bGkS1NLAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e849b91d6e131859d1be01f510ba4c1dec25f22214b6584b57bb9cdddfd32ba","last_reissued_at":"2026-07-05T09:52:29.252213Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:52:29.252213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.15740","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":"2026-07-05T09:52:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8KZV9x9ur1vl4/eup5A2TK2LMnvIeLUDpAkP2nzEoyX1e4aMXjyF76lF3Za/sT76gNoVyjzxmbHOewBmtyXQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:45:33.794270Z"},"content_sha256":"a55c32b15268ff0907075dfee437329a13443e2ec75a33bdc4b112cac79ded0a","schema_version":"1.0","event_id":"sha256:a55c32b15268ff0907075dfee437329a13443e2ec75a33bdc4b112cac79ded0a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:B2CJXEOW4EYYLHI34APVCC5EYH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel, Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Veronika Spieker","submitted_at":"2024-12-20T10:00:36Z","abstract_excerpt":"Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration is to precisely capture the deformation between two or more images, typically achieved by minimizing an optimization problem. Due to its inherent ill-posedness, regularization is a key component in driving the solution toward anatomically meaningful deformations. A wide range of regularization methods has been proposed for both conventional and deep learning-based registration. However, the appropriate application of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.15740","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/2412.15740/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":"2026-07-05T09:52:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y5z0JKq1B06yWA/L8bN/14XtYphiNYfbreolFSu/zmEsESiEkChCtfezFxz9Mu5PDeayUnBZ+zBkHMW8VM95DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:45:33.795053Z"},"content_sha256":"fe1ec5a9fdccf0afe43f2971596ef83901b1aae1160215605d1654b878851c42","schema_version":"1.0","event_id":"sha256:fe1ec5a9fdccf0afe43f2971596ef83901b1aae1160215605d1654b878851c42"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B2CJXEOW4EYYLHI34APVCC5EYH/bundle.json","state_url":"https://pith.science/pith/B2CJXEOW4EYYLHI34APVCC5EYH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B2CJXEOW4EYYLHI34APVCC5EYH/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":"2026-08-04T02:45:33Z","links":{"resolver":"https://pith.science/pith/B2CJXEOW4EYYLHI34APVCC5EYH","bundle":"https://pith.science/pith/B2CJXEOW4EYYLHI34APVCC5EYH/bundle.json","state":"https://pith.science/pith/B2CJXEOW4EYYLHI34APVCC5EYH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B2CJXEOW4EYYLHI34APVCC5EYH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:B2CJXEOW4EYYLHI34APVCC5EYH","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":"ebaa0bd339cf11657e167795e35252d35d417e9c9c653be0da99a006dbc3c669","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-12-20T10:00:36Z","title_canon_sha256":"77d1c1452fb7529c6776e5e75c598b642ae43aeef53586a80460ce23d955152c"},"schema_version":"1.0","source":{"id":"2412.15740","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.15740","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"arxiv_version","alias_value":"2412.15740v1","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.15740","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_12","alias_value":"B2CJXEOW4EYY","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_16","alias_value":"B2CJXEOW4EYYLHI3","created_at":"2026-07-05T09:52:29Z"},{"alias_kind":"pith_short_8","alias_value":"B2CJXEOW","created_at":"2026-07-05T09:52:29Z"}],"graph_snapshots":[{"event_id":"sha256:fe1ec5a9fdccf0afe43f2971596ef83901b1aae1160215605d1654b878851c42","target":"graph","created_at":"2026-07-05T09:52:29Z","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/2412.15740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration is to precisely capture the deformation between two or more images, typically achieved by minimizing an optimization problem. Due to its inherent ill-posedness, regularization is a key component in driving the solution toward anatomically meaningful deformations. A wide range of regularization methods has been proposed for both conventional and deep learning-based registration. However, the appropriate application of ","authors_text":"Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel, Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Veronika Spieker","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-12-20T10:00:36Z","title":"From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.15740","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:a55c32b15268ff0907075dfee437329a13443e2ec75a33bdc4b112cac79ded0a","target":"record","created_at":"2026-07-05T09:52:29Z","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":"ebaa0bd339cf11657e167795e35252d35d417e9c9c653be0da99a006dbc3c669","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-12-20T10:00:36Z","title_canon_sha256":"77d1c1452fb7529c6776e5e75c598b642ae43aeef53586a80460ce23d955152c"},"schema_version":"1.0","source":{"id":"2412.15740","kind":"arxiv","version":1}},"canonical_sha256":"0e849b91d6e131859d1be01f510ba4c1dec25f22214b6584b57bb9cdddfd32ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e849b91d6e131859d1be01f510ba4c1dec25f22214b6584b57bb9cdddfd32ba","first_computed_at":"2026-07-05T09:52:29.252213Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:52:29.252213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i5HMekV7cR9ohGSlC4gKr/bTYsMQtvWFwsOxuFkcVGAOD3CAbr2Ww5EymJw1vpUCgz90CwIM6ov35bGkS1NLAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:52:29.252637Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.15740","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a55c32b15268ff0907075dfee437329a13443e2ec75a33bdc4b112cac79ded0a","sha256:fe1ec5a9fdccf0afe43f2971596ef83901b1aae1160215605d1654b878851c42"],"state_sha256":"66d52d6a6beea07f2c815d3e0263f0cf1470d3bc17f13f33f7e40ad9f42093ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JVmVKbZSHvLJ5VhrSBRQwXE38y9CccqkxoXUKlgHUc4orSMS71qkegU11DOnjKoaC4IDVSq5+5txMF1DOc1xDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T02:45:33.803827Z","bundle_sha256":"0d66e2f69640f530cc306c31d45bf28fcfb03f3e36d2ad6f685eea3f93c3c1cc"}}