基于区域生长和阈值理论的脑白质分割

Min Li, Hongyan Luo, Renbin He, Wenwu Zhu, L. Tan, Yi Wu
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引用次数: 1

摘要

为了减少现有人体横切面图像分割方法中大量的人工干预,本文根据人脑横切面图像的特点,提出了一种基于正态灰度直方图区域增长和阈值理论的分割算法。更确切地说,这些切片图像最初是通过区域生长进行粗分割的。然后采用正态灰度直方图阈值法对图像进行细化分割。实验结果表明,该算法能准确有效地分割脑白质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation of White Matter Based on Region Growing and Threshold Theory
In order to reduce the massive manual intervention involved in the existing segmentation methods for human cross-section slice images, a segmentation algorithm based on the theory of region growing and threshold in normal gray histogram was proposed in this paper, according to the features of slice images of human brain. More exactly, these slice images were initially segmented coarsely by means of the region growing. Then the method of threshold in normal gray histogram was adopted to refine the segmentation. The experimental results indicate that the proposed algorithm can segment white matter accurately and effectively.
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