Abstract

The core objective of our paper is to compare K means clustering and watershed algorithm using MATLAB tool. The comparison is based on their performance, accuracy, and its geometrical dimension. A Brain tumour is one of the major cause of death in current space. Many researchers and scientist are constantly working from last two decades and proposing, unlike algorithm which can be integrated with biotechnology field for effective results. MRI image plays a predominant role in identifying and extracting the tumour part. It offers better results of various soft tissues as compared to CT scan, X-ray, and Ultrasound. Segmentation of image is a grueling task because of intensities. It is implied that patient survival can be increased if tumour is identified exactly at an early stage. A Brain tumour is an assembly of deviant cells which causes irritation, brain swelling, change in hearing and vision, change in muscle movement etc. In this paper, we are proposing the most effective algorithm for the tumour detection and identification. For implementation purpose, we used MATLAB toolbox of image processing.

Authors and Affiliations