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Liver Segmentation in Ultrasound Images Based on FCM_I

机译:基于FCM_I的超声图像中肝脏分割

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摘要

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.
机译:超声波检查是一项常规检查技术。它有几个优点,例如对人体没有伤害,便宜和相对高精度检查。因此它广泛用于体检和各种类型的器官检查。为了提高超声图像中肝病的检测率,本文提出了一种从超声图像中提取肝脏区域的方法。该方法首先涉及超声图像的不均匀照明,这使得图像中的肝脏区域的亮度是一致的。然后,为了更好地抵抗噪声,提出了使用称为FCM_I的先验形状信息的模糊C均值(FCM)方法来分割图像。最后,根据肝脏的分布和形状,获得图像中的最大前景区域。所提出的方法在医院获得的腹部超声图像中获得良好的结果。

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