Liver Segmentation in Ultrasound Images Based on FCM_I

Abstract

Ultrasonic examination is a routine inspection technology. It has several merits, such as no harm to human body, cheap and relative high precision inspection. So it is widely used in physical examination and various types of organ inspections. In order to increase the detection rate of liver disease in ultrasound images, a method extracting the liver region from ultrasound images is proposed in this paper. This method firstly deals with uneven illumination of ultrasound image, which makes the brightness of liver region in images to be consistent. Then, in order to better resist the noise, the Fuzzy C Mean (FCM) method using the priori shape information, which is called FCM_I, is proposed to segment the image. Finally, according to the distribution and shape of the liver, the largest foreground area in the image is obtained. The proposed method obtains good results in the abdominal ultrasound images obtained by the hospital.