{"title":"A constrained optimization approach for ultrasound shear wave speed estimation with time-lateral plane cleaning in medical imaging","authors":"MD Jahin Alam, Md. Kamrul Hasan","doi":"10.1016/j.health.2025.100423","DOIUrl":null,"url":null,"abstract":"<div><div>Ultrasound shear wave elastography (SWE) is a noninvasive tissue stiffness measurement technique for medical diagnosis. In SWE, an acoustic radiation force creates shear waves (SW) throughout a medium where the shear wave speed (SWS) is related to the medium stiffness. Traditional SWS estimation techniques are not noise-resilient in handling jitter and reflection artifacts. This paper proposes new techniques to estimate SWS in both time and frequency domains. These new methods utilize loss functions which are: (1) optimized by lateral signal shift between known locations, and (2) constrained by neighborhood displacement group shift determined from the time-lateral plane-denoised SW propagation. The proposed constrained optimization is formed by coupling neighboring particles’ losses with a Gaussian kernel, giving an optimum arrival time for the center particle to enforce local stiffness homogeneity and enable noise resilience. The explicit denoising scheme involves isolating SW profiles from time-lateral planes, creating parameterized masks. Additionally, lateral interpolation is performed to enhance reconstruction resolution and thereby improve the reliability of optimization. The proposed scheme is evaluated on a simulation (US-SWS-Digital-Phantoms) and three experimental phantom datasets: (i) Mayo Clinic CIRS049 model, (ii) RSNA-QIBA-US-SWS, (iii) Private data. The constrained optimization performance is compared with three time-of-flight (ToF) and two frequency-domain methods. The evaluations produced visually and quantitatively superior and noise-robust reconstructions compared to classical methods. Due to the quality and minimal error of SWS map formation, the proposed technique can find its application in tissue health inspection and cancer diagnosis.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":"8 ","pages":"Article 100423"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442525000425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ultrasound shear wave elastography (SWE) is a noninvasive tissue stiffness measurement technique for medical diagnosis. In SWE, an acoustic radiation force creates shear waves (SW) throughout a medium where the shear wave speed (SWS) is related to the medium stiffness. Traditional SWS estimation techniques are not noise-resilient in handling jitter and reflection artifacts. This paper proposes new techniques to estimate SWS in both time and frequency domains. These new methods utilize loss functions which are: (1) optimized by lateral signal shift between known locations, and (2) constrained by neighborhood displacement group shift determined from the time-lateral plane-denoised SW propagation. The proposed constrained optimization is formed by coupling neighboring particles’ losses with a Gaussian kernel, giving an optimum arrival time for the center particle to enforce local stiffness homogeneity and enable noise resilience. The explicit denoising scheme involves isolating SW profiles from time-lateral planes, creating parameterized masks. Additionally, lateral interpolation is performed to enhance reconstruction resolution and thereby improve the reliability of optimization. The proposed scheme is evaluated on a simulation (US-SWS-Digital-Phantoms) and three experimental phantom datasets: (i) Mayo Clinic CIRS049 model, (ii) RSNA-QIBA-US-SWS, (iii) Private data. The constrained optimization performance is compared with three time-of-flight (ToF) and two frequency-domain methods. The evaluations produced visually and quantitatively superior and noise-robust reconstructions compared to classical methods. Due to the quality and minimal error of SWS map formation, the proposed technique can find its application in tissue health inspection and cancer diagnosis.