Spatial mapping of acoustic impedance of shrimp scale using multiple overlap discrete wavelet transform (moDWT)

There are lots of challenges associated with conventional optical observation of biological tissues, where specimens are typically sliced and stained for better contrast. In contrast, Scanning Acoustic Microscopy (SAM) is a versatile label-free imaging technology widely applied in various domains, including biomedical imaging, non-destructive testing, and material research. It excels in offering precise visualization of both surface and subsurface structures, providing valuable insights through visual inspection and quantitative analysis. Acknowledging the SAM, this paper presents acoustic impedance microscopy of the shrimp scale in a novel manner. The proposed technique aims to image the local distribution of cross-sectional acoustic impedance in biological tissue, which is a parameter closely related to sound speed and potentially valuable for tissue characterization. The study leverages advanced signal processing techniques, maximal overlap discrete wavelet transform (moDWT), to decompose acoustic responses effectively. The moDWT, with its ability to handle signals of various lengths without constraints, is highlighted as a promising approach. To determine shrimp scale impedance, we first establish the accuracy of the proposed algorithm using PVDF as the target and polyimide as reference material. The results indicate an algorithm accuracy exceeding 90%. An impedance map is generated through Gaussian process regression (GPR), which predicts the impedance over the complete domain, addressing spatial variations in biological specimens. The resulting acoustic impedance maps provide in-depth insights into the functional framework and advance our understanding of shrimp biomechanics.