摘要
通过分析几种常用的医学图像分割评价方法,提出了一种新型的评价方法。此方法不仅能有效地反映出分割结果相比目标轮廓线的偏差量,还能反映出轮廓线附近的波动状况。再者,此方法的结果不仅能横向比较(比较不同算法对同一目标的分割结果),还能纵向比较(比较同一算法对不同目标的分割结果)。实验结果证明,本文提出的评价方法具有良好的临床价值。
An improved evaluation method for medical image segmentation is presented ,by analyzing several widely used evaluation methods. The new method can not only reflect how much the segmentation result is deviated from the object,but also indicate the degree of fluctuation near the contour. Furthermore, this method can be used for both parallel comparison, comparing the results of different algorithms operating on the same object, and longitudinal comparison, comparing the results of the same algorithm operating on different objects. The experiment results show that the proposed evaluation method has good clinical value.
出处
《北京生物医学工程》
2008年第4期385-388,共4页
Beijing Biomedical Engineering
基金
安徽省教委自然科学基金重点研究项目(2006KJ097A)资助
关键词
医学图像
分割评价
距离比较
medical image
segmentation evaluation
distance measure
