{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:ZYHIFFDCVVBUNH2OU7AAB3U6X2","short_pith_number":"pith:ZYHIFFDC","schema_version":"1.0","canonical_sha256":"ce0e829462ad43469f4ea7c000ee9ebe9b07668b43b17e0798a1f9ba7eb044ca","source":{"kind":"arxiv","id":"1608.04330","version":1},"attestation_state":"computed","paper":{"title":"Voxel-Based Dose Prediction with Multi-Patient Atlas Selection for Automated Radiotherapy Treatment Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Chris McIntosh, Thomas G. Purdie","submitted_at":"2016-08-15T17:04:31Z","abstract_excerpt":"Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography (CT) planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those at"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1608.04330","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-08-15T17:04:31Z","cross_cats_sorted":[],"title_canon_sha256":"68eb87aa8382ac47ee5d67a4febd7b126c49f660de96f6b8c634358ee2669152","abstract_canon_sha256":"0724b1958140be0e3d92bdc6d99fa4d4fac2aa2c1f94e264089236602c00f51c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:53:30.582374Z","signature_b64":"92hvgdTSR6/6Ycr38JGsaMB+qQEItbrEBIoZYVgTohwvQCqHBkZOMNPQ/rK8qQ2gbL2Y2ANjWTWfGcQOuMpSDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce0e829462ad43469f4ea7c000ee9ebe9b07668b43b17e0798a1f9ba7eb044ca","last_reissued_at":"2026-05-18T00:53:30.581973Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:53:30.581973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Voxel-Based Dose Prediction with Multi-Patient Atlas Selection for Automated Radiotherapy Treatment Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Chris McIntosh, Thomas G. Purdie","submitted_at":"2016-08-15T17:04:31Z","abstract_excerpt":"Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography (CT) planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those at"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.04330","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1608.04330","created_at":"2026-05-18T00:53:30.582036+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.04330v1","created_at":"2026-05-18T00:53:30.582036+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.04330","created_at":"2026-05-18T00:53:30.582036+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZYHIFFDCVVBU","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZYHIFFDCVVBUNH2O","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZYHIFFDC","created_at":"2026-05-18T12:30:55.937587+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2","json":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2.json","graph_json":"https://pith.science/api/pith-number/ZYHIFFDCVVBUNH2OU7AAB3U6X2/graph.json","events_json":"https://pith.science/api/pith-number/ZYHIFFDCVVBUNH2OU7AAB3U6X2/events.json","paper":"https://pith.science/paper/ZYHIFFDC"},"agent_actions":{"view_html":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2","download_json":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2.json","view_paper":"https://pith.science/paper/ZYHIFFDC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.04330&json=true","fetch_graph":"https://pith.science/api/pith-number/ZYHIFFDCVVBUNH2OU7AAB3U6X2/graph.json","fetch_events":"https://pith.science/api/pith-number/ZYHIFFDCVVBUNH2OU7AAB3U6X2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2/action/storage_attestation","attest_author":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2/action/author_attestation","sign_citation":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2/action/citation_signature","submit_replication":"https://pith.science/pith/ZYHIFFDCVVBUNH2OU7AAB3U6X2/action/replication_record"}},"created_at":"2026-05-18T00:53:30.582036+00:00","updated_at":"2026-05-18T00:53:30.582036+00:00"}