Monitoring Thermal Coagulation with Ultrasonic Textures

The feasibility of using B-mode ultrasound image textures and pattern recognition technique to characterize the thermal coagulation in vitro during radiofrequency ablation was investigated. The changes of ultrasonic textures in the different regions of samples varied with the heating time in the in-vitro experiments, which would result in that the coagulated and noncoagulated regions of tissue had different ultrasonic textures. Using support vector machine to extract the ultrasonic texture features and characterize the state of tissue, the size and boundaries of thermal lesions could be detected and measured more exactly than only using the gray scale information of B-mode ultrasound image. The proposed method would be applied to the image-guided radiofrequency ablation (IGRA) procedure for monitoring the thermal coagulation.     

Speckle reduction based on contourlet transform using scale adaptive threshold for medical ultrasound image

A new speckle suppression method in contourlet domain was presented. By modeling the subband contourlet coefficients of the ultrasound images after logarithmic transform as generalized Gaussian distribution (GGD), we gave a scale-adaptive threshold in Bayesian framework. Experimental results of both synthetic and clinical ultrasound images show that our method has a better performance on speckle suppressing than the wavelet-based method while well preserving the feature details.