Research On Ultrasound Frequency Characteristics And Imaging Algorithms Of Biological Tissue

Medical diagnosis is based on the interaction between ultrasound and tissue in the propagation of human body.It can extract information that can reflect the tissue status from the received signal,and display it intuitively with images or other forms,so as to achieve the purpose of diagnosis.Ultrasound diagnosis involves a lot of software and hardware systems and technology theories,including signal processing,imaging algorithms,defect analysis etc.Signal processing and imaging technology is the key to improve the quality of ultrasonic diagnosis.Ultrasonic frequency domain analysis can obtain more useful information than conventional test;coded excitation and beamforming technology are the effective methods to improve the quality of imaging.Therefore,in order to extract more tissue information from the signal,improve the quality of ultrasound imaging and the accuracy of ultrasound diagnosis,we researched the two aspects: ultrasonic frequency characteristic analysis and imaging algorithms.In view of the frequency characteristic analysis of ultrasonic signals,firstly,the ultrasonic transmission attenuation model is constructed according to the propagation mechanism of ultrasonic transmission in tissue,and the relationship between ultrasonic attenuation and tissue characteristics and frequency.The simulation results show that the proposed model is suitable for the range of measured values of ultrasonic attenuation in the tissue and can be applied to the theoretical analysis of the tissue characteristics.Secondly,the ultrasonic frequency characteristic analysis system is established by the ultrasonic frequency attenuation characteristic of biological tissue.Finally,simulation experiments show that the ultrasonic frequency response analysis based on attenuation model has a high recognition rate for different tissues.The thickness and type of tissue can be judged by waveform and frequency distribution,which provides a new basis and method for ultrasonic diagnosis.In medical imaging system,the resolution,contrast and signal to noise ratio(SNR)are important indexes to measure the quality of ultrasonic imaging.In the traditional pulse imaging,the resolution and contrast are difficult to reconcile,but the coded incentive can deal with the contradiction well.In order to improve the quality of ultrasonic imaging,the following methods are adopted in this paper.First,a coded excitation imaging algorithm based on predistortion processing is proposed.On the one hand,the method can compensate the influence of transducer impulse response on the transmit signal,so the bandwidth of echo signal is not limited by the transducer and the imaging resolution is improved;on the other hand,the composite modulated Chirp-Barker coded signal is adopted to improve the SNR of the imaging system and the resolution of ultrasound imaging while ensuring imaging contrast.Secondly,an ultrasonic imaging algorithm based on the minimum variance beamforming involving forward-backward characteristic space and coherence coefficient is proposed.The algorithm realizes the dynamic weighted value calculation of the echo data through the adaptive beamforming,and improves the resolution of the ultrasonic imaging.At the same time,the robustness and contrast of the traditional adaptive beamforming are improved by introducing the robust algorithm and the coherent coefficient method.The simulation results show that the image resolution and contrast of the algorithm are better than the existing algorithms.Finally,combining the coded excitation technology with the adaptive beamforming algorithm,an ultrasound imaging algorithm based on predistortion coded excitation and improved minimum variance beamforming is proposed.The algorithm improves the imaging quality of the system from both signal source and received data,so as to achieve better imaging results.