Brain Tumor Detection Using Image Processing

Brain Tumor Detection Using Image Processing

	© 2020 by IJCTT Journal
	Volume-68 Issue-4
	Year of Publication : 2020
	Authors : Priyanka Rawat
	DOI : 10.14445/22312803/IJCTT-V68I4P126

How to Cite?

Priyanka Rawat, "Brain Tumor Detection Using Image Processing," International Journal of Computer Trends and Technology, vol. 68, no. 4, pp. 159-164, 2020. Crossref, https://doi.org/10.14445/22312803/IJCTT-V68I4P126

Abstract
Medical image processing is the most demanding and emerging field now a days. MRI is an advanced medical technique providing information about the tissue present in the brain. Brain tumor is dangerous disease that affects the health and life of human being. The conventional method of detection and segmentation of brain tumor is done by human inspection. This process is so time consuming. So to avoid human intervention and save time, the application software of brain tumor detection and segmentation is develop. This research paper consists of Otsu method, k-means , fuzzy c means and morphological operations. All these techniques used in this paper shown great potential. Otsu method and k means are used for segmentation whereas morphological operations provide a systematic approaches to analyze the geometric characteristics of images and are widely used to many applications such as edge detection, noise suppression etc. This method successfully detect the presence of brain tumor with high accuracy. Morphological operations provide different features value used in detection of brain tumor. All these factors helps in extracting the useful information from MRI images. The combination of medical and information technology provides great achievement in both fields.

Keywords
MRI images, otsu’s method, k-means, fuzzy c-means, morphology and classification.

Reference
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Brain Tumor Detection Using Image Processing