Automatic Brain Tumour Detection using New Structure Algorithm
Mohammad Javeed1, M. Senthil Kumar2

1Mohammad Javeed, Assistant Professor, Dept. of ECE, Sree Dattha Institute of Engineering and Science, Hyderabad, Telangana, India.
2M. Senthil Kumar, Assistant Professor/HOD, Dept. of ECE, Sree Dattha Institute of Engineering and Science, Hyderabad, Telangana, India
Manuscript received on 22 August 2019. | Revised Manuscript received on 09 September 2019. | Manuscript published on 30 September 2019. | PP: 3402-3405 | Volume-8 Issue-11, September 2019. | Retrieval Number: K25360981119/2019©BEIESP | DOI: 10.35940/ijitee.K2536.0981119
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Abstract: 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.
Keywords: Segmentation, Structure Algorithm, K-Means algorithm, C-Means algorithm, Feature extraction, fuzzy K-Means clustering, edge detection, Brain tumor
Scope of the Article: Clustering