Microwave Ablation Monitoring Based On Automatic Segmentation Of Nakagami Parameter Imaging For Ultrasonic Harmonic Envelopes

Microwave ablation is an important method for the treatment of hepatocellular carcinoma.During microwave ablation surgery,effective monitoring of the ablation area is the key to successful surgery.The existing Nakagami parameter imaging of the ultrasonic harmonic envelope signal can realize non-invasive monitoring of the ablation process,but it cannot accurately estimate the ablation center and the ablation area.At present,there is no real-time,quantitative and accurate method for non-invasive monitoring of microwave ablation process,so the application and promotion of microwave ablation in clinical practice is limited.In this paper,a Gaussian approximation automatic segmentation（GAAS）method based on Nakagami parameters of ultrasonic harmonic envelope is proposed for accurate and effective monitoring of microwave ablation region.Firstly,the harmonic components of ultrasonic echo RF signal are obtained by high-pass filter.Next the Nakagami shape parameters of harmonic envelope were estimated,and composite window imaging was used to generate Nakagami parameter images.Nakagami image parameters are estimated gaussian approximation ablation area,then the approximation image of P-M,Catte and anisotropic smoothing pretreatment of Median algorithm and an adaptive threshold segmentation to obtain estimated ablation area,split after the estimate of the ablation area size and boundary are better than that of the Nakagami parameter estimation accuracy and visualization and estimates of the ablation area after gaussian approximation.In this paper,for validating the availability of the GAAS method,microwave ablation experiments were performed on 10 pig liver samples.The results of 10 experiments show that the long and short axes of the elliptical thermal damage region obtained by GAAS method are approximated with polynomials and then automatically segments to obtain the size comparison of the estimated ablation region.The Gaussian approximation image is preprocessed by smoothing based on P-M,Catte and Median algorithm,and then the smoothed image is segmented by adaptive threshold segmentation,watershed algorithm segmentation and pulse coupled neural network segmentation to obtain the estimated ablation region.The mean relative errors of the long and short axes between the estimated ablation area and the actual liver ablation area decreased by 17.53 % and 14.47 %,respectively.Compared with the result error after the pretreatment of three smoothing algorithms and the segmentation by watershed algorithm,the error between the long and short axes of the actual ablation region and the actual pig liver samples 1 and 2 after Median algorithm smoothing decreased by 2.28% and 2.30%.As for the result error of threshold segmentation,the mean error of the long and short axes of the result after watershed segmentation is reduced by 0.3% and 0.21%.In summary,GAAS using the Median algorithm for the ultrasonic harmonic envelope Nakagami parameter image can more accurately estimate the ablation area and boundary,and can effectively improve the monitoring performance of the degree and area of induced thermal damage.The GAAS method provides more accurate monitoring and better evaluation programs for clinical microwave ablation surgery.