{"doi":"10.1117/12.2647156","title":"Estimation of contrast agent concentration from pulsed-mode projections to time contrast-enhanced CT scans","abstract":"Cardiac CT exams are some of the most complex CT exams due to the need to carefully time the scan to capture the heart during a quiescent cardiac phase and when the intravenous contrast bolus is at its peak concentration in the left and/or right heart. We are interested in developing a robust and autonomous cardiac CT exam, using deep learning approaches to extract contrast and cardiac phase timing directly from projections. In this paper, we present a new approach to estimate contrast bolus timing directly from a sparse set of CT projections. We present a deep learning approach to estimate contrast agent concentration in left and right sides of the heart directly from a set of projections. We use a virtual imaging framework to generate training and test data, derived from real patient datasets. We finally combine this with a simple analytical approach to decide on the start of the cardiac CT exam.","journal":"7th International Conference on Image Formation in X-Ray Computed Tomography","year":2022,"id":299559,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9623,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":989442,"name":"Eri Haneda","orcid":"0000-0003-2660-9028","position":1,"is_corresponding":false},{"id":955341,"name":"Bernhard E. H. Claus","orcid":null,"position":2,"is_corresponding":false},{"id":854740,"name":"Jed D. Pack","orcid":"0000-0003-3232-1012","position":3,"is_corresponding":false},{"id":365032,"name":"Albert Hsiao","orcid":"0000-0002-9412-1369","position":4,"is_corresponding":false},{"id":535004,"name":"Elliot R. McVeigh","orcid":"0000-0003-1684-2432","position":5,"is_corresponding":false},{"id":357027,"name":"Bruno De Man","orcid":"0000-0001-7250-3406","position":6,"is_corresponding":false},{"id":989441,"name":"Isabelle Heukensfeldt Jansen","orcid":"0009-0004-6490-4882","position":0,"is_corresponding":true}],"reference_count":3,"raw_metadata":null,"created_at":"2026-07-19T00:31:44.904250Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}