DocumentCode :
3539404
Title :
A robust segmentation algorithm using morphological operators for detection of tumor in MRI
Author :
Ramya, L. ; Sasirekha, N.
Author_Institution :
Dept. of Electron. & Commun. Eng., Sona Coll. of Technol., Salem, India
fYear :
2015
fDate :
19-20 March 2015
Firstpage :
1
Lastpage :
4
Abstract :
Image Denoising and Image Segmentation are the two major areas of the medical image processing. The main objective of this paper is to develop a robust segmentation algorithm inorder to detect tumor in 2D MRI brain images. Here we use image denoising as the preprocessing step as noise plays an important role incase of accuracy of affected area of the image, especially in medical diagnostics. To denoise the image, fourth order partial differential equation is employed. A seeded region growing segmentation is used to detect the tumor in MRI brain image. Also skull removal procedure is employed using morphological operators to increase the accuracy of brain tumor detection. This method detects the tumor in the brain image efficiently and also tested for several brain tumor images.
Keywords :
biomedical MRI; brain; cancer; image denoising; image segmentation; medical image processing; partial differential equations; tumours; 2D MRI brain images; brain tumor detection; fourth order partial differential equation; image denoising; image segmentation; medical diagnostics; medical image processing; morphological operators; robust segmentation algorithm; seeded region growing segmentation; Biomedical imaging; Image denoising; Image segmentation; Magnetic resonance imaging; Noise; Partial differential equations; Tumors; Brain tumor; MRI; Region growing segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
Type :
conf
DOI :
10.1109/ICIIECS.2015.7192927
Filename :
7192927
Link To Document :
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