Segmentation of brain tumors in computed tomography images using SVM classifier

Author

Shanmugapriya, B. ; Ramakrishnan, T.

Author_Institution

Dept. of Electron. & Instrum., Nat. Eng. Coll., Kovilpatti, India

fYear

2014

fDate

13-14 Feb. 2014

Firstpage

1

Lastpage

3

Abstract

Medical image processing is an interdisciplinary field that has been attracted by various fields such as applied mathematics, computer science and engineering, biology and medicine etc. Due to the development of technologies in imaging modalities, more challenges arise, how to process and analyze a huge volume of images for the diagnosis of diseases and treatment procedure. In this Support Vector Machines (SVMs) has been used to segment the brain tumors in Computed Tomography (CT) images. The two Kernel function of the SVM has been compared in which the RBF-SVM outperforms the other one.

Keywords

brain; computerised tomography; diseases; image segmentation; medical image processing; radial basis function networks; support vector machines; tumours; Kernel function; RBF-SVM; SVM classifier; applied mathematics; biology; brain tumor segmentation; computed tomography images; computer science; disease diagnosis; engineering; imaging modalities; interdisciplinary field; medical image processing; medicine; support vector machines; treatment procedure; Accuracy; Image segmentation; Kernel; Medical diagnostic imaging; Polynomials; Support vector machines; CT; Polynomial; RBF; SVM; Segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics and Communication Systems (ICECS), 2014 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-2321-2

Type

conf

DOI

10.1109/ECS.2014.6892709

Filename

6892709