基于水平集方法的脑MRI图像胼胝体分割

Putri Damayanti, Dini Yuniasri, R. Sarno, Aziz Fajar, Dewi Rahmawati
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引用次数: 3

摘要

胼胝体整合了人类大脑的左右半球。胼胝体分割的方法有很多种,但现有的分割算法需要多个步骤来分割图像。因此,我们提出了一种简单的水平集分割胼胝体的方法。我们使用水平集方法,因为它可以很容易地处理大脑的结构。该方法通过将曲线或曲面表示为更高的超维曲面的零水平,为处理拓扑轮廓的变化提供了数值解决方案。实验表明,采用水平集方法对胼胝体进行分割,得到的骰子相似系数(DSC)值为85.14%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Corpus Callosum Segmentation from Brain MRI Images Based on Level Set Method
Corpus callosum integrates left and right hemispheres of human brain. There are several methods for segmenting corpus callosum, but the existing algorithms need several steps to segment images. Therefore, we propose a simple method using level set method to segment corpus callosum. We use level set method as it can handle the structure of the brain easily. This method provides a numerical solution for processing changes in topological contours by representing a curve or surface as a zero level to a higher hyper-dimensional surface. This experiment shows that by implementing level set method to segment the corpus callosum produces Dice Similarity Coefficient (DSC) value of 85.14%.
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