Texture Analysis Of Liver Ultrasonic Images

Ultrasound image diagnosis is an important medical image diagnostic means like x-ray CT, isotope scanning and MRI. The Ultrasound image diagnosis can show the shape and frame of people's viscera with no-expense and intuitionistic, can livingly observe functions and activities of people's viscera. For it's cheapness and easy to handle, ultrasound image diagnosis has been the most common means for the examination of people's inside shapes and frames. However, compared with other medical images(e. g. CT and MRI), the quality of ultrasound images is relatively low. At present, the diagnosis is determined naturally, the conclusion of disease is influenced by doctors. Therefore, it is needed eagerly to improve ultrasound image diagnosis by using computer.In this paper, we studied the images of liver ultrasound images by contracting the theory of ultrasound, texture analysis, pattern recognition. We discussed the texture characteristics of liver and it's lows. Subsequently we validated this lows by using GLSM method to extract the texture characters. At last ,we classified and recognized the images by using valued closest distance classified method and k-average clustering classified method. Contraposing clinic assistant diagnosis, we did useful study.