Brain MRI segmentation for tumor detection using Grammatical Swarm based clustering algorithm

Author

Si, Tapas ; De, Arunava ; Bhattacharjee, Anup Kumar

Author_Institution

Dept. of CSE, B.U. Inst. of Eng., Bankura, India

fYear

2014

Firstpage

1196

Lastpage

1201

Abstract

This paper presents segmentation of brain´s Magnetic Resonance image for tumor detection using Grammatical Swarm based clustering algorithm. Grammatical Swarm is a variant of Grammatical Evolution which can generate computer programs. First, MR images of brain are de-noised using Discrete Wavelet Transform based soft-thresholding technique. Grammatical Swarm based clustering algorithm is developed to segment the de-noised images to separate the mass lesion or tumor from the non-diseased objects in the image.

Keywords

biomedical MRI; brain; discrete wavelet transforms; image denoising; image segmentation; object detection; pattern clustering; tumours; brain MRI segmentation; computer programs; discrete wavelet transform; grammatical evolution; grammatical swarm based clustering algorithm; image denoising; image segmentation; magnetic resonance image; mass lesion; nondiseased objects; soft-thresholding technique; tumor detection; Clustering algorithms; Equations; Image segmentation; Indexes; Magnetic resonance imaging; Partitioning algorithms; Tumors; Brain MRI; Discrete Wavelet Transform; Grammatical Swarm; Magnetic Resonance Image; Particle Swarm Optimizer; clustering; segmentation; soft thresholding; tumor;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on

Print_ISBN

978-1-4799-2395-3

Type

conf

DOI

10.1109/ICCPCT.2014.7055051

Filename

7055051