基于对称区域生长算法的超声医学图像分割方法

Segmentation of Ultrasonic Medical Image Based on A Symmetric Region Growing Algorithm

提出了一种基于对称区域生长算法的超声医学图像的分割方法。该方法分为三步。首先,通过采用自适应加权中值滤波抑制超声医学图像本身固有的Speckle噪声,然后从图像的第一行开始扫描整个图像,并应用生长准则进行区域的生长与合并,生长完成之后应用种子准则标定感兴趣区域,从而得到最后的分割结果。通过图像的分割实验确定了一套对于超声医学图像适用的生长和合并准则。对心脏B型超声医学图像分割的实验结果显示,该方法具有良好的性能。

A method based on a symmetric region growing algorithm is presented for the segmentation of ultrasonic medical image. The method divides into three steps. First, according to the characteristic of the ultrasonic medical images, an adaptive weighted median filter is used to suppress speckle noise. Then, scan the digital image from the first row and grow regions from each scanned point by applying the growth criteria and combination criteria until all image pixels have been scanned. Examine the resulting regions using the seed criteria. If any point of a region satisfies the criteria for the region of interest region, assign the region to the resulting segmented image. The effectiveness of this method and a group of growth criteria as well as combination criteria applicable to ultrasonic medical image have been obtained by cardiac ultrasound image segmentation experiments. The experiment result shows that this method is good in the performance of the segmention of cardiac ultrasonic medical image.