A restarted iterative homotopy analysis method for three-dimensional image segmentation

Lavdie Rada, Ke Chen, B. Ghanbari
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引用次数: 1

Abstract

Total variational segmentation models provide effective tools for identifying all features and their boundaries in two and three dimensional images and have been proven to be useful and successful. Speeding up a simulation is one of the remaining challenges. In this paper we propose a restarted homotopy analysis method to improve the computational efficiency in three-dimensional image segmentation. The algorithm replaces the nonlinear variational problem by a sequence of linear approximations by working with linear equations instead of nonlinear ones which lead to efficient energy minimization while maintaining the segmentation quality. Experimental results will show that the computational efficiency is significantly improved.
一种三维图像分割的重启迭代同伦分析方法
总变分分割模型为识别二维和三维图像中的所有特征及其边界提供了有效的工具,并已被证明是有用和成功的。加速模拟是剩下的挑战之一。为了提高三维图像分割的计算效率,提出了一种重启同伦分析方法。该算法将非线性变分问题替换为一系列线性逼近问题,利用线性方程代替非线性方程,在保证分割质量的同时有效地实现了能量最小化。实验结果表明,该方法大大提高了计算效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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