{"doi":"10.1109/tuson.2025.3638314","title":"Labeled Numerical Phantom of Abdominal Wall for Wave-Physics-Based Ultrasound Imaging: Applications to Image Reconstruction","abstract":"Transabdominal ultrasound imaging requires acoustic wave propagation through the abdominal wall, which consists of a complex organization of tissue layers that degrade imaging of underlying organs such as the liver. A priori knowledge of the acoustic properties of this medium could enable adaptive imaging techniques, but the underlying ground truth properties in a living patient is a fundamentally unknown quantity. Numerical simulations can offer a solution to this challenge by modeling the propagation of ultrasound imaging pulses in media with known acoustic properties and can therefore provide a quantitative relationship between the received ultrasound echoes and the underlying tissue structure. However, to be comparable with clinical scenarios, in silico phantoms of the abdominal wall must be geometrically and quantitatively accurate, with rigorous tolerances. Here, we describe a dataset generation approach to produce experimentally calibrated ultrasound data for transabdominal imaging. Semantically labeled 3D in silico phantoms with 0.33mm isotropic resolution, along with physical parameters from the literature of the human abdominal wall, are used to model acoustic propagation through human tissue. We perform 2D numerical simulations of the Westervelt equation to generate a dataset of raw ultrasound data for liver imaging consisting of 1027 samples. We then discuss the applications of this dataset for facilitating abdominal ultrasound imaging research. The labeled abdominal dataset, simulated data, and the simulation tools that model wave propagation are made publicly available.","journal":"IEEE Transactions on Ultrasonics","year":2025,"id":537443,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9504,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1124657,"name":"Oleksii Ostras","orcid":"0000-0001-5200-5792","position":1,"is_corresponding":false},{"id":1423242,"name":"Masashi Sode","orcid":"0000-0002-3685-7378","position":2,"is_corresponding":false},{"id":1170205,"name":"Walter Simson","orcid":"0000-0002-2801-8646","position":3,"is_corresponding":false},{"id":452710,"name":"Dongwoon Hyun","orcid":"0000-0003-2625-8109","position":4,"is_corresponding":false},{"id":383567,"name":"Francisco Santibáñez","orcid":"0000-0002-6959-4148","position":5,"is_corresponding":false},{"id":284657,"name":"Jeremy Dahl","orcid":"0000-0001-9877-452X","position":6,"is_corresponding":false},{"id":383568,"name":"Gianmarco Pinton","orcid":"0000-0002-4896-1439","position":7,"is_corresponding":false},{"id":1170204,"name":"Louise Zhuang","orcid":"0000-0002-5677-4895","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:52:12.997494Z","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":[]}