2021/09/20 by Noushin Jafarpisheh, Iván M. Rosado-Méndez, Jafarpisheh, Noushin +5
Engineering · Medicine · #FOS: Electrical engineering #Signal Processing (eess.SP) #Ultrasonics and Acoustic Wave Propagation #Ultrasound Imaging and Elastography #Ultrasound and Hyperthermia Applications #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2109.09900
openalex publication_date 2021/09/20 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Quantitative ultrasound (QUS) parameters such as the effective scatterer\ndiameter (ESD) reveal tissue properties by analyzing ultrasound backscattered\necho signal. ESD can be attained through parametrizing backscatter coefficient\nusing form factor models. However, reporting a single scatterer size cannot\naccurately characterize a tissue, particularly when the media contains\nscattering sources with a broad range of sizes. Here we estimate the\nprobability of contribution of each scatterer size by modeling the measured\nform factor as a linear combination of form factors from individual sacatterer\nsizes. We perform the estimation using two novel techniques. In the first\ntechnique, we cast scatterer size distribution as an optimization problem, and\nefficiently solve it using a linear system of equations. In the second\ntechnique, we use the solution of this system of equations to constrain the\noptimization function, and solve the constrained problem. The methods are\nevaluated in simulated backscattered coefficients using Faran theory. We\nevaluate the robustness of the proposed techniques by adding Gaussian noise.\nThe results show that both methods can accurately estimate the scatterer size\ndistribution, and that the second method outperforms the first one.\n