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首页> 外文会议>2010 IEEE International Workshop on Medical Measurements and Applications Proceedings >Medical image segmentation - a comparison of two algorithms
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Medical image segmentation - a comparison of two algorithms

机译：医学图像分割-两种算法的比较

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摘要

Image segmentation plays an important role in image analysis as a frequent pre-processing step in many image understanding algorithms and practical vision systems. According to several authors, segmentation terminates when the observer's goal is satisfied and for this reason, a unique method that can be applied to all possible cases does not yet exist. The purpose of this paper is to find which segmentation method is more appropriate for recognition and diagnosis of medical images. The algorithms used for comparison are: the color set back-projection algorithm that can be found in many related studies, and an original segmentation method using a hexagonal structure defined on the set of image pixels. Error measuring algorithms, which quantify the consistency between these two segmentations, were used in order to evaluate these segmentation methods. These measures allow a principled comparison between segmentation results on different images, with differing numbers of regions and which is generated by different algorithms with different parameters.
机译：在许多图像理解算法和实际视觉系统中，图像分割作为频繁的预处理步骤在图像分析中起着重要的作用。根据几位作者的说法，分割在观察者的目标得到满足时终止，因此，尚不存在可应用于所有可能情况的独特方法。本文的目的是找到哪种分割方法更适合医学图像的识别和诊断。用于比较的算法有：在许多相关研究中都可以找到的颜色集反投影算法，以及使用在图像像素集上定义的六边形结构的原始分割方法。为了评估这些分割方法，使用了量化这两个分割之间一致性的误差测量算法。这些措施允许在具有不同区域数量的不同图像上的分割结果之间进行原则上的比较，这是由具有不同参数的不同算法生成的。

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