Title: Brain tumour segmentation in MRI: knowledge-based system and region growing approach

Authors: Badredine Sayah; Bornia Tighiouart

Addresses: Department of Computer Science, LRI Laboratory, Badji Mokhtar, Annaba University, 23000, Algeria ' Department of Computer Science, LRI Laboratory, Badji Mokhtar, Annaba University, 23000, Algeria

Abstract: We present in this paper a method for MRI brain tumour segmentation, so we propose a general framework that is a combination of paradigms, in order to have a hybrid segmentation method, automatic and unsupervised. In the first phase, expertise and characteristics derived from MRI images are combined to define heuristics for the development of the classification approach. In the second phase, refinement of the tumour contour is achieved by using the region growing method. The results are good and visually validated by radiologists.

Keywords: brain imaging; MRI; brain tumour segmentation; fuzzy logic; fuzzy classification; region growing; knowledge-based systems; KBS; magnetic resonance imaging; brain tumours.

DOI: 10.1504/IJBET.2014.059060

International Journal of Biomedical Engineering and Technology, 2014 Vol.14 No.1, pp.71 - 89

Received: 03 Jan 2013
Accepted: 12 Dec 2013
Published online: 16 Oct 2014 *

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