Brain tumor severity analysis using modified multi-texton histogram and hybrid kernel SVM

Author:

Jayachandran A.1,Dhanasekaran R.2

Affiliation:

1. PSN College of Engineering and Technology; Tirunelveli Tamil Nadu India

2. Syed Ammal Engineering College; Ramanathapuram Tamil Nadu India

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Reference32 articles.

1. F. Admasua S.A. Zubia K. Toenniesa N. Bodammerb H. Hinrichsb Segmentation of multiple sclerosis lesions from MR brain images using the principles of fuzzy-connectedness and artificial neuron networks 2003

2. Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI;Ahmed;IEEE Trans Inf Technol Biomed,2011

3. A multichannel Markov random field framework for tumor segmentation with an application to classification of gene expression-based breast cancer recurrence risk;Ashraf;IEEE Trans Med Imaging,2013

4. Fully automatic segmentation of brain tumor images using support vector machine classification in combination with hierarchical conditional random field regularization;Bauer;MICCAI,,2011

5. Introduction to support vector machines;Boswell;Proc World Acad Sci Eng Technol,2002

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