Viscoelastic Estimation of Soft Tissue in the Presence of Gaussian and Reflection Noises Impacting Shear Wave Propagation

Shear wave elastography images of soft tissues are essential tools for early diagnosis disease tumor in medical applications, including breast cancer, thyroid gland conditions, and prostate assessments, among others. These images provide doctor with several benefits, such as rapid results, cost-effectiveness, and remarkable reliability. However, obtaining high-quality ultrasound images of elastic tissues requires effective noise reduction techniques, particularly when dealing with Gaussian and reflection noises during shear wave measurements. In our research, we explore a comprehensive approach to estimate elasticity and viscosity using a directional filter using a directional filter to effectively eliminate reflection noise and an adaptive LMS filter to significantly reduce Gaussian noise. We then apply the AHI algorithm to precisely estimate the viscoelastic properties of soft tissue. These innovations not only enhance image quality but also show great promise in improving diagnostic accuracy in critical medical situations.