Objective evaluation of medical image segmentation algorithms is one of the important steps toward establishing validity and clinical applicability of an algorithm. Since there are a large number of articles presenting segmentation methods on medical image

with few studying the evaluation methods on their performance

this paper presents an evaluation method for different segmentation algorithms. The author first gives a survey of several available evaluation methods and presents a systematic summary. Reliability

precision

region statistical characteristics and efficiency are the four most important metrics. The definitions of them are then described based on the image segmentation process. For comparison

weights should be added to these metrics according to the application. Moreover

the author also presents a method on how to construct gold standard of medical images. At last

with the task of brain white matter segmentation

the author demonstrates how to make use of the proposed evaluation method to compare two segmentation algorithms in insight toolkit（ITK). The experiment results show that this method is practical and reasonable. This study gives a scientific method for the evaluation of segmentation algorithms on medical image. Meanwhile

it points out the problems to be solved before the segmentation algorithms could be put into use in clinic.