DocumentCode
1686184
Title
Implementation of an improved cellular neural network algorithm for brain tumor detection
Author
Abdullah, Azian Azamimi ; Chize, Bu Sze ; Nishio, Yoshifumi
Author_Institution
Sch. of Mechatron. Eng., Univ. Malaysia Perlis (UniMAP), Arau, Malaysia
fYear
2012
Firstpage
611
Lastpage
615
Abstract
Image processing plays an important role in medical diagnosis. In this paper, a brain tumor detection method based on cellular neural networks (CNNs) is proposed. Brain tumor is an abnormal growth of cells inside the skull. To examine the location of tumor in the brain, Magnetic Resonance Imaging (MRI) is used. Radiologists will evaluate the grey scale MRI images. This procedure is really time and energy consuming. To overcome this problem, an automated detection method for brain tumor using CNN is developed. By using the template in the CNN simulator, output of the desired image can be performed. Therefore, many templates were combined in order to obtain an accurate result that will help radiologists detecting the tumor in brain images easily.
Keywords
biomedical MRI; brain; cellular biophysics; cellular neural nets; medical image processing; tumours; automated detection method; brain tumor detection; cells; cellular neural network algorithm; grey scale MRI images; image processing; magnetic resonance imaging; medical diagnosis; skull; Algorithm design and analysis; Brain; Cellular neural networks; Image segmentation; Magnetic resonance imaging; Signal processing algorithms; Tumors; Brain tumor; MRI images; cellular neural network; image processing; templates;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering (ICoBE), 2012 International Conference on
Conference_Location
Penang
Print_ISBN
978-1-4577-1990-5
Type
conf
DOI
10.1109/ICoBE.2012.6178990
Filename
6178990
Link To Document