ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2019
Hierarchical Motion Estimation With Bayesian Regularization in Cardiac Elastography: Simulation and In Vivo Validation.
Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Lagrangian deformation tracking for strain imaging.Progress in biomedical engineering (Bristol, England) · 2026Review
- Development of a Predictive Statistical Pharmacological Model for Local Anesthetic Agent Effects with Bayesian Hierarchical Model Parameter Estimation.Medicines (Basel, Switzerland) · 2023Article
- In Vivo Adaptive Bayesian Regularized Lagrangian Carotid Strain Imaging for Murine Carotid Arteries and Its Associations With Histological Findings.Ultrasound in medicine & biology · 2023Article
- Preliminary Feasibility of Stress Myocardial Elastography for the Detection of Coronary Artery Disease.Ultrasound in medicine & biology · 2023Article
- In Vivo Longitudinal Monitoring of Cardiac Remodeling in Murine Ischemia Models With Adaptive Bayesian Regularized Cardiac Strain Imaging: Validation Against Histology.Ultrasound in medicine & biology · 2023Article
- Murine cardiac fibrosis localization using adaptive Bayesian cardiac strain imaging in vivo.Scientific reports · 2022Article
- Bayesian Regularized Strain Imaging for Assessment of Murine Cardiac Function In vivo.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Subaperture Processing-Based Adaptive Beamforming for Photoacoustic Imaging.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021Article
- Spatiotemporal Bayesian Regularization for Cardiac Strain Imaging: Simulation andIEEE open journal of ultrasonics, ferroelectrics, and frequency control · 2021Article
- Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020Article
- Locally optimized correlation-guided Bayesian adaptive regularization for ultrasound strain imaging.Physics in medicine and biology · 2020Article
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4 authors.
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Abstract
Cardiac elastography (CE) is an ultrasound-based technique utilizing radio-frequency (RF) signals for assessing global and regional myocardial function. In this work, a complete strain estimation pipeline for incorporating a Bayesian regularization-based hierarchical block-matching algorithm, with Lagrangian motion description and myocardial polar strain estimation is presented. The proposed regularization approach is validated using finite-element analysis (FEA) simulations of a canine cardiac deformation model that is incorporated into an ultrasound simulation program. Interframe displacements are initially estimated using a hierarchical motion estimation framework. Incremental displacements are then accumulated under a Lagrangian description of cardiac motion from end-diastole (ED) to end-systole (ES). In-plane Lagrangian finite strain tensors are then derived from the accumulated displacements. Cartesian to cardiac coordinate transformation is utilized to calculate radial and longitudinal strains for ease of interpretation. Benefits of regularization are demonstrated by comparing the same hierarchical block-matching algorithm with and without regularization. Application of Bayesian regularization in the canine FEA model provided improved ES radial and longitudinal strain estimation with statistically significant ( ) error reduction of 48.88% and 50.16%, respectively. Bayesian regularization also improved the quality of temporal radial and longitudinal strain curves with error reductions of 78.38% and 86.67% ( ), respectively. Qualitative and quantitative improvements were also visualized for in vivo results on a healthy murine model after Bayesian regularization. Radial strain elastographic signal-to-noise ratio (SNR
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