Image Quality Measurement of Independent Linear Matrix-Based Decomposition Results and Attenuation Coefficients

Abstract

One way to diagnosing a disease is by examining an image. To display an image on a specific component, an inverse matrix-based algorithmic decomposition technique is used. If the Lambert-Beer Law equation is subjected to a natural logarithmic operation, a linear relationship between intensity level and thickness will be produced. Furthermore, an image can be displayed based on the thickness function. By varying three different wavelengths and three different materials, three types of linear equations are obtained. This variation in wavelength affects the level of decomposition. The results show that the combination of 780 nm-808 nm-980 nm wavelengths is better in quality than other wavelength variations. In this study, a phantom composed of silicone rubber, margarine, and gelatin was used. This phantom material is representative of the human body material.