{"doi":"10.1109/tuffc.2020.2983732","title":"3-D X-Ray-Induced Acoustic Computed Tomography With a Spherical Array: A Simulation Study on Bone Imaging","abstract":"X-ray-induced acoustic computed tomography (XACT) is a promising imaging modality combining high X-ray absorption contrast with the 3-D propagation advantages provided by high-resolution ultrasound waves. The purpose of this study was to optimize the configuration of a 3-D XACT imaging system for bone imaging. A 280 ultrasonic sensors with peak frequency of 10 MHz was designed to distribute on a spherical surface to optimize the 3-D volumetric imaging capability. We performed both theoretical calculations and simulations of this optimized XACT imaging configuration on a mouse-sized digital phantom containing various X-ray absorption coefficients. Iteration algorithm based on total variation has been used for 3-D XACT image reconstruction. The spatial resolution of imaging was estimated to about [Formula: see text] along both axial and lateral directions. We simulate XACT imaging of bone microstructures using digital phantoms generated from micro-CT images of real biological samples, showing that XACT imaging can provide high-resolution imaging of the mouse paw. Results of this study will greatly enhance the potential of XACT imaging in the evaluation of bone diseases for future clinical use.","journal":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","year":2020,"id":76313,"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":21,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9639,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":397905,"name":"Pratik Samant","orcid":"0000-0002-9550-3502","position":1,"is_corresponding":false},{"id":397906,"name":"Siqi Wang","orcid":"0000-0001-6136-2492","position":2,"is_corresponding":false},{"id":397907,"name":"Ali Behrooz","orcid":"0000-0002-6576-3119","position":3,"is_corresponding":false},{"id":397908,"name":"Dengwang Li","orcid":"0000-0001-5126-3888","position":4,"is_corresponding":false},{"id":397909,"name":"Liangzhong Xiang","orcid":"0000-0002-7228-0510","position":5,"is_corresponding":false},{"id":397904,"name":"Yang Li","orcid":"0000-0002-9544-5840","position":0,"is_corresponding":true}],"reference_count":42,"raw_metadata":null,"created_at":"2026-07-18T21:47:46.469293Z","pmid":"32286967","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":[]}