Application of Morphological Operations in Human Brain CT Image With SVM

Author

Fallahi, Ali Reza ; Pooyan, Mohammad ; Mohammadnejad, Hojat

Author_Institution

Dept. of Biomed. Eng., Shahed Univ., Tehran, Iran

fYear

2009

fDate

11-13 June 2009

Firstpage

1

Lastpage

4

Abstract

In this paper, computer aided diagnosis is applied to the brain CT image processing. We compared performance of morphological operations in extracting three types of features i.e. gray scale, symmetry and texture. SVM, MLPNN and RBFNN are used to build classifiers for normal and abnormal brain CT image. It shows that morphological operation can improve the accuracy. Moreover, method of SVM has better result than MLP and RBF neural network.

Keywords

brain; computerised tomography; feature extraction; image texture; medical image processing; multilayer perceptrons; neurophysiology; pattern classification; radial basis function networks; support vector machines; CT classifier; CT image processing; MLPNN network; RBF neural network; SVM morphological operation; gray scale feature extraction; human brain CT image; image texture; multilayer perceptron neural network; support vector machine; Biomedical imaging; Computed tomography; Feature extraction; Filters; Humans; Medical diagnostic imaging; Morphological operations; Pathology; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2901-1

Electronic_ISBN

978-1-4244-2902-8

Type

conf

DOI

10.1109/ICBBE.2009.5162390

Filename

5162390