{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:LUTSLKRSMZZA76T6MDHCJ54NKJ","short_pith_number":"pith:LUTSLKRS","schema_version":"1.0","canonical_sha256":"5d2725aa3266720ffa7e60ce24f78d5251ae81b066e2291a0afdd13d132c8aff","source":{"kind":"arxiv","id":"1801.09533","version":1},"attestation_state":"computed","paper":{"title":"Statistical Image Reconstruction Using Mixed Poisson-Gaussian Noise Model for X-Ray CT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"physics.med-ph","authors_text":"Jeffrey A. Fessler, Qiaoqiao Ding, Xiaoqun Zhang, Yong Long","submitted_at":"2018-01-19T05:41:39Z","abstract_excerpt":"Statistical image reconstruction (SIR) methods for X-ray CT produce high-quality and accurate images, while greatly reducing patient exposure to radiation. When further reducing X-ray dose to an ultra-low level by lowering the tube current, photon starvation happens and electronic noise starts to dominate, which introduces negative or zero values into the raw measurements. These non-positive values pose challenges to post-log SIR methods that require taking the logarithm of the raw data, and causes artifacts in the reconstructed images if simple correction methods are used to process these non"},"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":"1801.09533","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2018-01-19T05:41:39Z","cross_cats_sorted":["math.NA"],"title_canon_sha256":"772be66bdcdb1647db7b6290ce02b9f761331ddd0710b3253a16c103ac09c332","abstract_canon_sha256":"53b676fa8e0e83df2c6277f716556f61e2d0f1cd71fb1f5f68bf1dbf5ad7286f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:57.141019Z","signature_b64":"p0XYCJyW7OSJBSs1Qwaafzs38N1r8HMWD+YCv0im1EdxqwHQmr77cncqZcEe2HIYF1sW3EjtKVaQsyvsdGx5Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d2725aa3266720ffa7e60ce24f78d5251ae81b066e2291a0afdd13d132c8aff","last_reissued_at":"2026-05-18T00:24:57.140310Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:57.140310Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Statistical Image Reconstruction Using Mixed Poisson-Gaussian Noise Model for X-Ray CT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"physics.med-ph","authors_text":"Jeffrey A. Fessler, Qiaoqiao Ding, Xiaoqun Zhang, Yong Long","submitted_at":"2018-01-19T05:41:39Z","abstract_excerpt":"Statistical image reconstruction (SIR) methods for X-ray CT produce high-quality and accurate images, while greatly reducing patient exposure to radiation. When further reducing X-ray dose to an ultra-low level by lowering the tube current, photon starvation happens and electronic noise starts to dominate, which introduces negative or zero values into the raw measurements. These non-positive values pose challenges to post-log SIR methods that require taking the logarithm of the raw data, and causes artifacts in the reconstructed images if simple correction methods are used to process these non"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.09533","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":"1801.09533","created_at":"2026-05-18T00:24:57.140446+00:00"},{"alias_kind":"arxiv_version","alias_value":"1801.09533v1","created_at":"2026-05-18T00:24:57.140446+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.09533","created_at":"2026-05-18T00:24:57.140446+00:00"},{"alias_kind":"pith_short_12","alias_value":"LUTSLKRSMZZA","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_16","alias_value":"LUTSLKRSMZZA76T6","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_8","alias_value":"LUTSLKRS","created_at":"2026-05-18T12:32:37.024351+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2604.17208","citing_title":"CDSA-Net:Collaborative Decoupling of Vascular Structure and Background for High-Fidelity Coronary Digital Subtraction Angiography","ref_index":50,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ","json":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ.json","graph_json":"https://pith.science/api/pith-number/LUTSLKRSMZZA76T6MDHCJ54NKJ/graph.json","events_json":"https://pith.science/api/pith-number/LUTSLKRSMZZA76T6MDHCJ54NKJ/events.json","paper":"https://pith.science/paper/LUTSLKRS"},"agent_actions":{"view_html":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ","download_json":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ.json","view_paper":"https://pith.science/paper/LUTSLKRS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1801.09533&json=true","fetch_graph":"https://pith.science/api/pith-number/LUTSLKRSMZZA76T6MDHCJ54NKJ/graph.json","fetch_events":"https://pith.science/api/pith-number/LUTSLKRSMZZA76T6MDHCJ54NKJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ/action/storage_attestation","attest_author":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ/action/author_attestation","sign_citation":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ/action/citation_signature","submit_replication":"https://pith.science/pith/LUTSLKRSMZZA76T6MDHCJ54NKJ/action/replication_record"}},"created_at":"2026-05-18T00:24:57.140446+00:00","updated_at":"2026-05-18T00:24:57.140446+00:00"}