## 4 Conclusions  
The radial artery contains the richest physiological and pathological information related to the entire circulatory system of the human body. Since traditional digital signal processing methods cannot process large amounts of ultrasound data in real time, and the CORDIC algorithm is superior in calculating complex functions, this paper applies the CORDIC algorithm to the entire ultrasound signal processing. Considering the shortcomings of the classical CORDIC algorithm and the computational requirements of the signal processing, this article focuses on the research of dynamic filtering technology based on the radix-4 CORDIC, quadrature demodulation technology based on the partitioned-hybrid CORDIC algorithm, and dynamic range transformation technology based on the improved scale-free CORDIC algorithm. The accuracy of each module's algorithm is then verified separately based on the FPGA. The filter coefficient error of the dynamic FIR filtering module does not exceed \(4\times 10^{-3}\), can effectively filter out high-frequency signals, retain low-frequency signals, remove noise, and achieve a stop-band attenuation of over \(-50\) dB with a good filtering effect. The absolute error in the square simulation results is of order \(10^{-3}\), and the absolute error of the logarithmic simulation is of order \(10^{-3}\). So the accuracy of the data processed by each module can meet the requirements of ultrasound imaging. To ensure the repeatability and reliability of the experiment, the probe is positioned parallel and perpendicular to the radial artery to collect data from 20 volunteers several times. The experimental results show that the radial artery ultrasound imaging system based on CORDIC provides a clear picture of the radial artery vessels and that the readings match the actual vessel diameters. It also verifies the effectiveness of the ultrasound signal processing technology based on the high-performance CORDIC algorithm in radial artery ultrasound imaging, which lays the foundation for computer-aided medical diagnosis. In this paper, the focus is only on the three key links of radial artery ultrasound signal processing in combination with three CORDIC algorithms. The application of other improved CORDIC algorithms to radial artery ultrasound signal processing is still worth exploring. In addition, the CORDIC algorithm is not limited to ultrasound signal processing modules. It can also be applied to fast and accurate delay control of ultrasound emission/reception focusing modules, as well as fast spatial coordinate conversion for 3D ultrasound image reconstruction. Further research into the performance advantages of the CORDIC algorithm in radial artery ultrasound imaging is planned for the future. It will ultimately reduce system development costs, improve overall system stability and real-time reconstruction of radial artery ultrasound images, and achieve the goal of computer-aided diagnosis of human health conditions. Conceptualization, C.Z. and X.G. ; methodology, C.Z. ; software, C.Z. and X.G. ; validation, C.Z., X.G. and F.Y. ; data collection, C.Z., L.L. and Z.G. ; data analysis, C.Z. ; writing--original draft preparation, C.Z. ; writing--review and editing, C.Z. and X.G. ; final approval, C.Z., X.G., L.L., Z.G., Y.W., F.Y. and Y.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by the National key Research and Development Program, grant no. 2022 YFC3502300 provides necessary financial support for data acquisition and algorithm verification. Figure 13: Comparison of radial artery diameters in subjects with different scanning modalities of the probe. (**a**) Men; (**b**)Women. **Institutional Review Board Statement:** Ethical review and approval were waived for this study due to the research we conducted was only to collect pulse wave signals on the surface of the body. It did not cause any physiological harm to the volunteers and did not involve the privacy of the volunteers.