{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UGH6A2CYD3G6CC3BBN3EDTXPIN","short_pith_number":"pith:UGH6A2CY","canonical_record":{"source":{"id":"2403.06801","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-11T15:17:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3da96e6eaecf29769c64d3e89d079a1cabcbaff4fc40503e6fc7c9432695a2e7","abstract_canon_sha256":"cb6bedbf33fc5ac234ceba428ead0de6c56ada6840348ca2c626e041f590a220"},"schema_version":"1.0"},"canonical_sha256":"a18fe068581ecde10b610b7641ceef437807d3e2008e8973fb7198848b357950","source":{"kind":"arxiv","id":"2403.06801","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06801","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06801v2","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06801","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_12","alias_value":"UGH6A2CYD3G6","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_16","alias_value":"UGH6A2CYD3G6CC3B","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_8","alias_value":"UGH6A2CY","created_at":"2026-07-05T08:40:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UGH6A2CYD3G6CC3BBN3EDTXPIN","target":"record","payload":{"canonical_record":{"source":{"id":"2403.06801","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-11T15:17:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3da96e6eaecf29769c64d3e89d079a1cabcbaff4fc40503e6fc7c9432695a2e7","abstract_canon_sha256":"cb6bedbf33fc5ac234ceba428ead0de6c56ada6840348ca2c626e041f590a220"},"schema_version":"1.0"},"canonical_sha256":"a18fe068581ecde10b610b7641ceef437807d3e2008e8973fb7198848b357950","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:40:14.723520Z","signature_b64":"qyQKLkZCbFWYLOoHQHBfrtH9DUrEse0Wq0vwel+POlUkVRFd4rmC2KPan2+IytlY6o05DEHZnmDSAcIk0a2xBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a18fe068581ecde10b610b7641ceef437807d3e2008e8973fb7198848b357950","last_reissued_at":"2026-07-05T08:40:14.722993Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:40:14.722993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.06801","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:40:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"71ij4p4t3r/LZLwuEXSliqG+73jPDF5c2l2OaKHqPVGnq6/LEvxveJ6FfvzYzTId22jB0oZ8k1ktZwIkcPOZBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T14:27:01.597774Z"},"content_sha256":"f0f72c914719ee345db4be0333789c65828cde29ef9e12ba115500adaf9619c5","schema_version":"1.0","event_id":"sha256:f0f72c914719ee345db4be0333789c65828cde29ef9e12ba115500adaf9619c5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UGH6A2CYD3G6CC3BBN3EDTXPIN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Bjoern Menze, Ibrahim Ethem Hamamci, Sezgin Er","submitted_at":"2024-03-11T15:17:45Z","abstract_excerpt":"Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital documentation. Automating report generation has emerged as a critical need to alleviate the workload of radiologists. While machine learning has facilitated report generation for 2D medical imaging, extending this to 3D has been unexplored due to computational complexity and data scarcity. We introduce the first method to generate radiology reports for 3D medical imaging, specifically targeting chest CT volumes. Given the absence of comparable methods, we establish a baseline using an advanced 3D vision "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06801","kind":"arxiv","version":2},"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/2403.06801/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":"2026-07-05T08:40:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0VTArxIiHraetSALI/ar+I/mf9GzVU+DtFOyd/Tpn+YVq+aVwECuUwgYdEQX1gx5HRU4lzrD5aeyF0u/AKf/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T14:27:01.598265Z"},"content_sha256":"b054c366699182674b5eb70cf0c2ab7670bbe0e556fd43c25ddab1e79c8b867c","schema_version":"1.0","event_id":"sha256:b054c366699182674b5eb70cf0c2ab7670bbe0e556fd43c25ddab1e79c8b867c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/bundle.json","state_url":"https://pith.science/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/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":"2026-08-05T14:27:01Z","links":{"resolver":"https://pith.science/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN","bundle":"https://pith.science/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/bundle.json","state":"https://pith.science/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UGH6A2CYD3G6CC3BBN3EDTXPIN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UGH6A2CYD3G6CC3BBN3EDTXPIN","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":"cb6bedbf33fc5ac234ceba428ead0de6c56ada6840348ca2c626e041f590a220","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-11T15:17:45Z","title_canon_sha256":"3da96e6eaecf29769c64d3e89d079a1cabcbaff4fc40503e6fc7c9432695a2e7"},"schema_version":"1.0","source":{"id":"2403.06801","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06801","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06801v2","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06801","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_12","alias_value":"UGH6A2CYD3G6","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_16","alias_value":"UGH6A2CYD3G6CC3B","created_at":"2026-07-05T08:40:14Z"},{"alias_kind":"pith_short_8","alias_value":"UGH6A2CY","created_at":"2026-07-05T08:40:14Z"}],"graph_snapshots":[{"event_id":"sha256:b054c366699182674b5eb70cf0c2ab7670bbe0e556fd43c25ddab1e79c8b867c","target":"graph","created_at":"2026-07-05T08:40:14Z","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/2403.06801/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital documentation. Automating report generation has emerged as a critical need to alleviate the workload of radiologists. While machine learning has facilitated report generation for 2D medical imaging, extending this to 3D has been unexplored due to computational complexity and data scarcity. We introduce the first method to generate radiology reports for 3D medical imaging, specifically targeting chest CT volumes. Given the absence of comparable methods, we establish a baseline using an advanced 3D vision ","authors_text":"Bjoern Menze, Ibrahim Ethem Hamamci, Sezgin Er","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-11T15:17:45Z","title":"CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06801","kind":"arxiv","version":2},"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:f0f72c914719ee345db4be0333789c65828cde29ef9e12ba115500adaf9619c5","target":"record","created_at":"2026-07-05T08:40:14Z","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":"cb6bedbf33fc5ac234ceba428ead0de6c56ada6840348ca2c626e041f590a220","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-11T15:17:45Z","title_canon_sha256":"3da96e6eaecf29769c64d3e89d079a1cabcbaff4fc40503e6fc7c9432695a2e7"},"schema_version":"1.0","source":{"id":"2403.06801","kind":"arxiv","version":2}},"canonical_sha256":"a18fe068581ecde10b610b7641ceef437807d3e2008e8973fb7198848b357950","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a18fe068581ecde10b610b7641ceef437807d3e2008e8973fb7198848b357950","first_computed_at":"2026-07-05T08:40:14.722993Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:40:14.722993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qyQKLkZCbFWYLOoHQHBfrtH9DUrEse0Wq0vwel+POlUkVRFd4rmC2KPan2+IytlY6o05DEHZnmDSAcIk0a2xBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:40:14.723520Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.06801","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0f72c914719ee345db4be0333789c65828cde29ef9e12ba115500adaf9619c5","sha256:b054c366699182674b5eb70cf0c2ab7670bbe0e556fd43c25ddab1e79c8b867c"],"state_sha256":"0fef4598c2f6e4089adff30f4922fa5ecfa8e51f0d8deed554ff27e9bb8434a3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uGr7fhy/Og5DeMODkW4mpPa39H9EBSpDB9BBqvkKMCC7rUdY2XHCCxIVG4FOgSfFJN0Xcet/T7cMSJtmw+s+Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T14:27:01.601705Z","bundle_sha256":"b4227c57422c2d8fd3fcb65e9fe7a4dc68c44a9458bb13156769d91085226f6d"}}