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IJSTR >> Volume 9 - Issue 1, January 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Effective Detection Of Brain Tumour On MRI Images Using Optimization Based Segmentation Techniques

[Full Text]

 

AUTHOR(S)

Rajesh Babu, K. Khanal Madhava Prasad, K. Rahul Krishna, M. Gowtham Samhith, P. Jameema Pushpitha, K. Kundana Gowri

 

KEYWORDS

Brain tumour, Magnetic Resonance image (MRI), Pre-Processing; Genetic algorithm, Particle Swarm Optimization, Dwained Particle Swarm Optimization

 

ABSTRACT

The medical image segmentation is a complex and stimulating task due to the distinct features of the images. To detect the brain tumour, it is one of the applications for brain image segmentation which is required and also pre-processing stage will be added to increase the detection accuracy. The segmentation for Magnetic Resonance Imaging (MRI) of brain is a difficult task due to the high quality of images, anatomical structures of the brain and complexity of tumors. In the field of medical imaging several researchers have made many algorithms in the field of tumor segmentation. This research work is comparing the results of Genetic algorithm (GA) with segmentation technique of Particle Swam Optimization (PSO) and segmentation technique of Particle Swam Optimization (PSO)With Darwinian Particle Swarm Optimization (DPSO). Using these three selected features, the accuracy of the dataset collected has been evaluated and the results are discussed, from these the paper. We compare these results with the Genetic Algorithm with PSO and PSO with DPSO algorithms, which are widely, used technique in the medical image analysis. The future work is measuring the size of the predicted tumor region, which provides more accuracy to the algorithms.

 

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