{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DQLHFOI223JVKKQGHYDVH4BLJU","short_pith_number":"pith:DQLHFOI2","canonical_record":{"source":{"id":"2410.22265","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T17:26:36Z","cross_cats_sorted":[],"title_canon_sha256":"17184e4c783e093f4064ef9701fadceccdba2c0847f155660d3198c8716e2de2","abstract_canon_sha256":"d4e01ce76b067efbd70a73317b6d3f7fc089798206e02e0e39a44004df63bd51"},"schema_version":"1.0"},"canonical_sha256":"1c1672b91ad6d3552a063e0753f02b4d1a4260825fad7769a076d0059115571c","source":{"kind":"arxiv","id":"2410.22265","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.22265","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.22265v1","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.22265","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_12","alias_value":"DQLHFOI223JV","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"DQLHFOI223JVKKQG","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"DQLHFOI2","created_at":"2026-07-05T09:28:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DQLHFOI223JVKKQGHYDVH4BLJU","target":"record","payload":{"canonical_record":{"source":{"id":"2410.22265","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T17:26:36Z","cross_cats_sorted":[],"title_canon_sha256":"17184e4c783e093f4064ef9701fadceccdba2c0847f155660d3198c8716e2de2","abstract_canon_sha256":"d4e01ce76b067efbd70a73317b6d3f7fc089798206e02e0e39a44004df63bd51"},"schema_version":"1.0"},"canonical_sha256":"1c1672b91ad6d3552a063e0753f02b4d1a4260825fad7769a076d0059115571c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:28:06.725176Z","signature_b64":"fB6XoZ8PxWUIptt0e0Btsaksz+sd9oF0LwFiUsUQrOMRLHImmRovzeCmLdKccby2NSR95/FpIUSP6/dzmz1EDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c1672b91ad6d3552a063e0753f02b4d1a4260825fad7769a076d0059115571c","last_reissued_at":"2026-07-05T09:28:06.724637Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:28:06.724637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.22265","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":"2026-07-05T09:28:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cDkKcxnA4SZDC3v5fLDKvi3aoGG7mkQqliOo717hStlQEEuEyugpJZkjM2z5Hp6DVLIYzEU+LtFaMFsPol9eCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T02:36:01.019476Z"},"content_sha256":"deb3b92a2b948bd0f3f81e8815ca91b4d441f18b5d380c2ba753a0db6c1e1635","schema_version":"1.0","event_id":"sha256:deb3b92a2b948bd0f3f81e8815ca91b4d441f18b5d380c2ba753a0db6c1e1635"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DQLHFOI223JVKKQGHYDVH4BLJU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NCA-Morph: Medical Image Registration with Neural Cellular Automata","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amin Ranem, Anirban Mukhopadhyay, John Kalkhof","submitted_at":"2024-10-29T17:26:36Z","abstract_excerpt":"Medical image registration is a critical process that aligns various patient scans, facilitating tasks like diagnosis, surgical planning, and tracking. Traditional optimization based methods are slow, prompting the use of Deep Learning (DL) techniques, such as VoxelMorph and Transformer-based strategies, for faster results. However, these DL methods often impose significant resource demands. In response to these challenges, we present NCA-Morph, an innovative approach that seamlessly blends DL with a bio-inspired communication and networking approach, enabled by Neural Cellular Automata (NCAs)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.22265","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/2410.22265/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":"2026-07-05T09:28:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jki3a8b3HQqw3P1Zr25dI8RRcWepsf/hWsYwVo7abhbB1gkBXm9T7IJF8eM8xrkxN8JvvKLOqggzdJTXyyaOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T02:36:01.019967Z"},"content_sha256":"0c40cac592cf35c4badf69688ca35491cffd7a794a17bba90dd6fc074658f09c","schema_version":"1.0","event_id":"sha256:0c40cac592cf35c4badf69688ca35491cffd7a794a17bba90dd6fc074658f09c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DQLHFOI223JVKKQGHYDVH4BLJU/bundle.json","state_url":"https://pith.science/pith/DQLHFOI223JVKKQGHYDVH4BLJU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DQLHFOI223JVKKQGHYDVH4BLJU/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":"2026-08-13T02:36:01Z","links":{"resolver":"https://pith.science/pith/DQLHFOI223JVKKQGHYDVH4BLJU","bundle":"https://pith.science/pith/DQLHFOI223JVKKQGHYDVH4BLJU/bundle.json","state":"https://pith.science/pith/DQLHFOI223JVKKQGHYDVH4BLJU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DQLHFOI223JVKKQGHYDVH4BLJU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DQLHFOI223JVKKQGHYDVH4BLJU","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":"d4e01ce76b067efbd70a73317b6d3f7fc089798206e02e0e39a44004df63bd51","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T17:26:36Z","title_canon_sha256":"17184e4c783e093f4064ef9701fadceccdba2c0847f155660d3198c8716e2de2"},"schema_version":"1.0","source":{"id":"2410.22265","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.22265","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"arxiv_version","alias_value":"2410.22265v1","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.22265","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_12","alias_value":"DQLHFOI223JV","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"DQLHFOI223JVKKQG","created_at":"2026-07-05T09:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"DQLHFOI2","created_at":"2026-07-05T09:28:06Z"}],"graph_snapshots":[{"event_id":"sha256:0c40cac592cf35c4badf69688ca35491cffd7a794a17bba90dd6fc074658f09c","target":"graph","created_at":"2026-07-05T09:28:06Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2410.22265/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical image registration is a critical process that aligns various patient scans, facilitating tasks like diagnosis, surgical planning, and tracking. Traditional optimization based methods are slow, prompting the use of Deep Learning (DL) techniques, such as VoxelMorph and Transformer-based strategies, for faster results. However, these DL methods often impose significant resource demands. In response to these challenges, we present NCA-Morph, an innovative approach that seamlessly blends DL with a bio-inspired communication and networking approach, enabled by Neural Cellular Automata (NCAs)","authors_text":"Amin Ranem, Anirban Mukhopadhyay, John Kalkhof","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T17:26:36Z","title":"NCA-Morph: Medical Image Registration with Neural Cellular Automata"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.22265","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:deb3b92a2b948bd0f3f81e8815ca91b4d441f18b5d380c2ba753a0db6c1e1635","target":"record","created_at":"2026-07-05T09:28:06Z","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":"d4e01ce76b067efbd70a73317b6d3f7fc089798206e02e0e39a44004df63bd51","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T17:26:36Z","title_canon_sha256":"17184e4c783e093f4064ef9701fadceccdba2c0847f155660d3198c8716e2de2"},"schema_version":"1.0","source":{"id":"2410.22265","kind":"arxiv","version":1}},"canonical_sha256":"1c1672b91ad6d3552a063e0753f02b4d1a4260825fad7769a076d0059115571c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c1672b91ad6d3552a063e0753f02b4d1a4260825fad7769a076d0059115571c","first_computed_at":"2026-07-05T09:28:06.724637Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:06.724637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fB6XoZ8PxWUIptt0e0Btsaksz+sd9oF0LwFiUsUQrOMRLHImmRovzeCmLdKccby2NSR95/FpIUSP6/dzmz1EDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:06.725176Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.22265","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:deb3b92a2b948bd0f3f81e8815ca91b4d441f18b5d380c2ba753a0db6c1e1635","sha256:0c40cac592cf35c4badf69688ca35491cffd7a794a17bba90dd6fc074658f09c"],"state_sha256":"5ed3fa660767f20e357d7b0150cd6893912046ba011d4ed5a8858325734ce42c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NAxgr2u31uJqzMSlUQqqQBf4+1anNRcJ5ZkmimwHIdw0dcHEDaEZoXUanzO2hZ9syBWv0gkqSBr//IgTwtEUBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T02:36:01.024039Z","bundle_sha256":"be9528f879b1ffcdfd4c41a90eea4b21cdcc6e5985820104f6c5e5fe95fe9fab"}}