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Liver Segmentation in Ultrasound Images Based on FCM_I

机译:基于FCM_I的超声图像肝分割

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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:超声波检查是一种常规检查技术。它具有对人体无伤害,价格便宜和相对高精度的优点。因此,它被广泛应用于身体检查和各种类型的器官检查。为了提高超声图像中肝脏疾病的检出率,提出了一种从超声图像中提取肝脏区域的方法。该方法首先处理超声图像的照度不均匀,使图像中肝脏区域的亮度保持一致。然后,为了更好地抵抗噪声,提出了一种使用先验形状信息的模糊C均值(FCM)方法,称为FCM_I,以对图像进行分割。最后,根据肝脏的分布和形状,获得图像中最大的前景区域。所提出的方法在医院获得的腹部超声图像中获得了良好的效果。

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