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

Authors: Nookala Venu; B. Anuradha

Addresses: Department of Electronics and Communication Engineering, Sri Venkateswara University, Tirupati 517502, India ' Department of Electronics and Communication Engineering, Sri Venkateswara University, Tirupati 517502, India

Abstract: 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.

Keywords: image segmentation; fuzzy c-means clustering; fuzzy logic; hyperbolic tangent function; spatial information; MRI segmentation; magnetic resonance imaging; medical images.

DOI: 10.1504/IJSISE.2016.076223

International Journal of Signal and Imaging Systems Engineering, 2016 Vol.9 No.3, pp.135 - 145

Received: 27 Jul 2013
Accepted: 18 Mar 2014
Published online: 30 Apr 2016 *

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