Multi-hyperbolic tangent fuzzy c-means algorithm with spatial information for MRI segmentation

被引：0

作者：

Venu, Nookala ^{[1
]}

Anuradha, B. ^{[1
]}

机构：

[1] Sri Venkateswara Univ, Dept Elect & Commun Engn, Tirupati 517502, Andhra Pradesh, India

来源：

INTERNATIONAL JOURNAL OF SIGNAL AND IMAGING SYSTEMS ENGINEERING | 2016年 / 9卷 / 03期

关键词：

segmentation; clustering algorithm; fuzzy; hyperbolic tangent function;

D O I：

10.1504/IJSISE.2016.076223

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a novel image segmentation using Multi-Hyperbolic Tangent Fuzzy C-Means (HTFCM) algorithm, with spatial information for medical image segmentation. The proposed method uses two hyperbolic tangent functions with the spatial information of neighbouring pixels for clustering of images. The performance of the proposed algorithm is tested on OASIS-MRI image data set. The performance is tested in terms of score, number of iterations (NI) and execution time (TM) under different Gaussian and salt & pepper noises on OASIS-MRI data set. The results after investigating the proposed method show a significant improvement as compared to other existing methods in terms of score, NI and TM under different Gaussian and salt & pepper noises on OASIS-MRI data set.

引用

页码：135 / 145

页数：11

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