The study of multiwavelength photoacoustic temperature measurement based on different weight factor algorithms

Abstract

Photoacoustic temperature measurement (PATM) is a real-time, non-contact, and high sensitivity method, which can satisfy the requirements of spatial and temperature resolution in clinical application. But PATM has been traditionally challenging to measure temperature without knowing the baseline temperature. Multiwavelength PATM is an effective way to improve this problem, but previous studies have only averaged measurements, so the improvements were limited. Therefore, aiming to further reduce the system error and improve the measurement accuracy and reliability of multiwavelength PATM, four different weight factor optimization methods, including the arithmetic mean, the coefficient of determination, the error variance, and the least squares, were studied in this paper. Using the basic theories of multiwavelength PATM and statistical optimization algorithm, the theoretical feasibility of optimization methods were analyzed. The ex-vivo tissue experimental results indicate that the optimization algorithm can effectively reduce the measurement error to 0.065 °C, which is almost five times higher than the conventional single wavelength method.

Keywords

• Multiwavelength photoacoustic temperature measurement
• Optimization algorithm
• Photoacoustic temperature measurement