Open AccessAutomatic Brain Tumour Detection using New Structure Algorithm
Author(s) -
Mohammad Javeed,
M.Senthil Kumar
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k2536.0981119
Subject(s) - thresholding , computer science , segmentation , artificial intelligence , edge detection , cluster analysis , image segmentation , pattern recognition (psychology) , computer vision , feature (linguistics) , fuzzy logic , process (computing) , region growing , feature extraction , point (geometry) , brain tumor , image processing , image (mathematics) , scale space segmentation , mathematics , medicine , pathology , linguistics , philosophy , geometry , operating system
Tumor is an abandoned development of tissues in any part of the body. Tumors have different treatment for different characteristics of tissues. Brain tumor is a very serious and dangerous, as we know. In developed countries most Research shows that due to the inaccurate detection of tumor many people have died. Normally, CT scan or MRI images will be used for the detection of tumor. In this research, we want to introduce a method which is very advanced and accurate for brain tumor detection based on a new structure algorithm. This technique focuses mainly on pre- processing, Edge detection, segmentation, Feature extraction. Pre-processing will be done first for filtering, after filtering edge detection is applied to the image, then after advanced fuzzy K- means (AFKM) clustering algorithm is used for the segmentation process. Finally thresholding will extract the tumor at a particular point in the image. This technique is very suitable for segmentation with exactness when we compare with the manual segmentation. In addition, it also shrinks the time for examination.