Szczegóły publikacji
Opis bibliograficzny
Enhanced shear wave attenuation estimation with expanded bandwidth in viscoelastic media / Piotr KIJANKA, Ramin ALMASI // Computers in Biology and Medicine ; ISSN 0010-4825. — 2025 — vol. 197 pt. B art. no. 111042, s. 1–11. — Bibliogr. s. 11, Abstr. — Publikacja dostępna online od: 2025-09-23
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 162930 |
|---|---|
| Data dodania do BaDAP | 2025-09-25 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.compbiomed.2025.111042 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Computers in Biology and Medicine |
Abstract
Ultrasound shear wave elastography (SWE) is widely employed to differentiate healthy from pathological tissues based on their viscoelastic mechanical properties. Although elasticity has traditionally been the main focus, tissue viscosity also plays a crucial role in characterizing mechanical behavior using SWE. Numerous methods have been developed for estimating the viscosity, with rheological model-based approaches being the most widely used. However, model-free techniques are gaining increasing attention, as they do not impose a predetermined relationship between wave velocity and attenuation, offering greater flexibility in capturing complex tissue viscoelastic behavior. In this study, we propose a novel method for calculating the shear wave attenuation. The approach, termed SAGA-ST, integrates a Super-Gaussian window-based Stockwell transform with slant frequency–wavenumber (f-k) analysis and leverages the full width at half-maximum of the f-k spectrum. The SAGA-ST method was first evaluated using analytical phantom data in tissue-mimicking viscoelastic media. To further assess its robustness, we applied the method to analytical shear wave motion data corrupted with varying levels of additive white Gaussian noise. Experimental validation was also performed using data from custom-designed tissue-mimicking phantoms and ex vivo bovine liver sample. We compared the performance of SAGA-ST with two existing techniques: the two-dimensional Fourier transform (2D-FT) and the generalized Stockwell transform-based method (GST-SFK). The proposed SAGA-ST method consistently demonstrates superior performance in analytical phantoms, exhibiting lower median attenuation bias and a smaller interquartile range. This is further supported by data points predominantly falling within the acceptable bias region and a median attenuation bias of less than 1% across all signal-to-noise ratio levels and frequency ranges, collectively indicating enhanced accuracy and precision. Furthermore, SAGA-ST extends the usable bandwidth for attenuation estimation, compared to the 2D-FT-based method, offering improved accuracy for tissue characterization.
