{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:6K5DWSFQOWPCLZ2WB3EW7P6KT5","short_pith_number":"pith:6K5DWSFQ","schema_version":"1.0","canonical_sha256":"f2ba3b48b0759e25e7560ec96fbfca9f407c9f7c18935463dc945667e61da520","source":{"kind":"arxiv","id":"1710.07028","version":1},"attestation_state":"computed","paper":{"title":"Image-domain multi-material decomposition for dual-energy CT based on correlation and sparsity of material images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"physics.med-ph","authors_text":"Qiaoqiao Ding, Tianye Niu, Xiaoqun Zhang, Yong Long","submitted_at":"2017-10-19T07:51:37Z","abstract_excerpt":"Dual energy CT (DECT) enhances tissue characterization because it can produce images of basis materials such as soft-tissue and bone. DECT is of great interest in applications to medical imaging, security inspection and nondestructive testing. Theoretically, two materials with different linear attenuation coefficients can be accurately reconstructed using DECT technique. However, the ability to reconstruct three or more basis materials is clinically and industrially important. Under the assumption that there are at most three materials in each pixel, there are a few methods that estimate multi"},"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":"1710.07028","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2017-10-19T07:51:37Z","cross_cats_sorted":["math.NA"],"title_canon_sha256":"d4f42900f674530fea800e082a4790b315921a2d4785b01f61edbaa059d86656","abstract_canon_sha256":"fd39fcfe66bc46655a7f8d0a242d49482a7f8f7a24fe48b49b452677e402d4cb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:41.333171Z","signature_b64":"vDZfY8t2VLvxKf/46arNnYUjzy5KvMaxDg+jfkRH3zzNI6bwW5Qb1QHUm8q9hs/wef7u3leIV8FySlEdlh+3DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2ba3b48b0759e25e7560ec96fbfca9f407c9f7c18935463dc945667e61da520","last_reissued_at":"2026-05-18T00:06:41.332624Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:41.332624Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Image-domain multi-material decomposition for dual-energy CT based on correlation and sparsity of material images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"physics.med-ph","authors_text":"Qiaoqiao Ding, Tianye Niu, Xiaoqun Zhang, Yong Long","submitted_at":"2017-10-19T07:51:37Z","abstract_excerpt":"Dual energy CT (DECT) enhances tissue characterization because it can produce images of basis materials such as soft-tissue and bone. DECT is of great interest in applications to medical imaging, security inspection and nondestructive testing. Theoretically, two materials with different linear attenuation coefficients can be accurately reconstructed using DECT technique. However, the ability to reconstruct three or more basis materials is clinically and industrially important. Under the assumption that there are at most three materials in each pixel, there are a few methods that estimate multi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.07028","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":"1710.07028","created_at":"2026-05-18T00:06:41.332726+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.07028v1","created_at":"2026-05-18T00:06:41.332726+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.07028","created_at":"2026-05-18T00:06:41.332726+00:00"},{"alias_kind":"pith_short_12","alias_value":"6K5DWSFQOWPC","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_16","alias_value":"6K5DWSFQOWPCLZ2W","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_8","alias_value":"6K5DWSFQ","created_at":"2026-05-18T12:31:03.183658+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/6K5DWSFQOWPCLZ2WB3EW7P6KT5","json":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5.json","graph_json":"https://pith.science/api/pith-number/6K5DWSFQOWPCLZ2WB3EW7P6KT5/graph.json","events_json":"https://pith.science/api/pith-number/6K5DWSFQOWPCLZ2WB3EW7P6KT5/events.json","paper":"https://pith.science/paper/6K5DWSFQ"},"agent_actions":{"view_html":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5","download_json":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5.json","view_paper":"https://pith.science/paper/6K5DWSFQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.07028&json=true","fetch_graph":"https://pith.science/api/pith-number/6K5DWSFQOWPCLZ2WB3EW7P6KT5/graph.json","fetch_events":"https://pith.science/api/pith-number/6K5DWSFQOWPCLZ2WB3EW7P6KT5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5/action/storage_attestation","attest_author":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5/action/author_attestation","sign_citation":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5/action/citation_signature","submit_replication":"https://pith.science/pith/6K5DWSFQOWPCLZ2WB3EW7P6KT5/action/replication_record"}},"created_at":"2026-05-18T00:06:41.332726+00:00","updated_at":"2026-05-18T00:06:41.332726+00:00"}