Brain Tumor Detection Using Soft Computing Tools
Journal: International Journal of Science and Research (IJSR) (Vol.5, No. 10)Publication Date: 2016-10-05
Authors : Nilakshi Devi; Prasanta Kr. Baruah. Kaustubh Bhattacharyya;
Page : 1882-1885
Keywords : Brain Tumor; MRI; Artificial Neural Network; Fuzzy Logic; Genetic Algorithm; Brain Image Segmentation; Soft Computing Tools;
Abstract
Modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. For brain tumor detection, image segmentation is required, which is a challenging task faced by todays medical neurologist. This is considered to be one of the most important step in detecting brain tumor as the further treatment and diagnosis depend on it. Hence, it is highly necessary that segmentation of the MRI images must be done accurately. Limitations in manual detection have made the researchers to turn their attention towards the using of soft computing tools in brain tumor detection. Over the years many researchers have proposed different methods of tumor detection using intelligent tools like ANN, Fuzzy Logic etc. obtaining better results. Here are discussed a few methods of brain tumor detection using different algorithms proposed by researchers.
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