{"doi":"10.1002/mrm.29812","title":"Optimization of 3D dynamic speech <scp>MRI</scp>: Poisson‐disc undersampling and locally higher‐rank reconstruction through partial separability model with regional optimized temporal basis","abstract":"PURPOSE: To improve the spatiotemporal qualities of images and dynamics of speech MRI through an improved data sampling and image reconstruction approach. METHODS: For data acquisition, we used a Poisson-disc random under sampling scheme that reduced the undersampling coherence. For image reconstruction, we proposed a novel locally higher-rank partial separability model. This reconstruction model represented the oral and static regions using separate low-rank subspaces, therefore, preserving their distinct temporal signal characteristics. Regional optimized temporal basis was determined from the regional-optimized virtual coil approach. Overall, we achieved a better spatiotemporal image reconstruction quality with the potential of reducing total acquisition time by 50%. RESULTS: The proposed method was demonstrated through several 2-mm isotropic, 64 mm total thickness, dynamic acquisitions with 40 frames per second and compared to the previous approach using a global subspace model along with other k-space sampling patterns. Individual timeframe images and temporal profiles of speech samples were shown to illustrate the ability of the Poisson-disc under sampling pattern in reducing total acquisition time. Temporal information of sagittal and coronal directions was also shown to illustrate the effectiveness of the locally higher-rank operator and regional optimized temporal basis. To compare the reconstruction qualities of different regions, voxel-wise temporal SNR analysis were performed. CONCLUSION: Poisson-disc sampling combined with a locally higher-rank model and a regional-optimized temporal basis can drastically improve the spatiotemporal image quality and provide a 50% reduction in overall acquisition time.","journal":"Magnetic Resonance in Medicine","year":2023,"id":362798,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9545,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":379448,"name":"Yudu Li","orcid":"0000-0003-2061-2306","position":1,"is_corresponding":false},{"id":900373,"name":"Ryan Shosted","orcid":null,"position":2,"is_corresponding":false},{"id":824029,"name":"Fangxu Xing","orcid":"0000-0002-0517-0952","position":3,"is_corresponding":false},{"id":889222,"name":"Imani Gilbert","orcid":"0000-0002-1810-011X","position":4,"is_corresponding":false},{"id":502877,"name":"Jamie L. Perry","orcid":"0000-0001-7866-9159","position":5,"is_corresponding":false},{"id":552607,"name":"Jonghye Woo","orcid":"0000-0002-5621-9218","position":6,"is_corresponding":false},{"id":379450,"name":"Zhi‐Pei Liang","orcid":"0000-0003-4586-3056","position":7,"is_corresponding":false},{"id":289297,"name":"Bradley P. Sutton","orcid":"0000-0002-8443-0408","position":8,"is_corresponding":false},{"id":899936,"name":"Riwei Jin","orcid":"0000-0002-2982-1123","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":null,"created_at":"2026-07-19T01:14:23.749325Z","pmid":"37677043","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":[]}