Brain Tumor Detection using Image Segmentation Techniques on MRI Images

Abstract

A refine and absolute detection of the human disease can increase the level for the survival of well being. One of the major diseases can be determine as cancer or brain tumor. Different technique used for the tumor detection such as MRI (Medical Resonance Image), Ultrasound etc. It does not involve the X-ray so there are not side effects of MRI. Claustrophobic sensation can occur with MRI scanning because of the close machine with the suffocation and no movement while the scan can increase the time to complete the scanning process while movement can cause the errors or edge distortion. An MRI or magnetic resonance imaging is a radiology technique scan that uses radio waves and with the help of computer to produce images of different body parts. MRI scanner is a tube surrounded by a giant circular magnet. The patient is placed on a moveable bed that is inserted into the magnet. The magnet creates a strong magnetic field that aligns the protons of hydrogen atoms, which are then exposed to a beam of radio waves. A computer receives the information, which produces an image. MRI is the most accurate and safe method to detect the diseases by detecting the slight change in the body. For the best result various image segmentation techniques and the good edge detection algorithms are used for finding the edge to get the effective images for the examination purpose of medical images.

Integrated approach of brain segmentation using neuro fuzzy k-means

“…Artificial neural networks (ANN) is yet another technique that is widely used in the medical imaging field. The supervised learning model is highly suitable for applications that do not require any assumptions based on prior distribution [17]. ANN plays a significant role in reducing the computation time and false Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  Integrated approach of brain segmentation using neuro fuzzy k-means (Jawwad Sami Ur Rahman) 271 recognition rate [18].…”