Analysis and Comparison of Brain TumorDetection and Extraction Techniques fromMRI Images

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering

article

Geetika Gupta¹  Rupinder Kaur¹  Arun Bansal²  Munish Bansal³ 

[1] Dept. of ECE, Doaba Institute of Engineering and Technology;AB Technologies;Chandigarh College of Engineering and Technology

关键词: Image processing;    MRI;    segmentation;    watershed segmentation;    CNN;    k-Means clustering;   

DOI  :  10.15662/ijareeie.2014.0311069

来源: Research & Reviews

【 摘 要 】

Magnetic Resonance Imaging (MRI) is the procedure used in hospitals to scan patients and determine the severity of certain injuries. It produces high quality images of the human body part. Tumors in various body parts are also scanned using MRI. Brain tumor is an abnormal cell formation within the brain leading to brain cancer. Thus it is very important to detect and extract brain tumor. The main thing behind the brain tumor detection and extraction from an MRI image is the image segmentation. Segmenting an image means dividing an image into regions based on some specific criteria. Various algorithms have been proposed for this purpose. This is a knowledge based review paper presenting a brief study of such algorithms highlighting their methodology and advantages and disadvantages if any.

【 授权许可】

Unknown