AUTOMATED CLASSIFICATION AND SEGREGATION OF BRAIN MRI IMAGES INTO IMAGES CAPTURED WITH RESPECT TO VENTRICULAR REGION AND EYE-BALL REGION

• Main Authors: C. Arunkumar, Sadam R. Husshine, V.P. Giriprasanth, Arun B. Prasath
• Format: Article
• Language: English
• Published: ICT Academy of Tamil Nadu 2014-05-01
• Series: ICTACT Journal on Image and Video Processing
• Subjects: Brain MRI Images; Automation in MRI; Ventricular Region; Eyeball Region
• Online Access: http://ictactjournals.in/paper/IJIVP_Paper_6-831_834.pdf

Magnetic Resonance Imaging (MRI) images of the brain are used for detection of various brain diseases including tumor. In such cases, classification of MRI images captured with respect to ventricular and eye ball regions helps in automated location and classification of such diseases. The methods employed in the paper can segregate the given MRI images of brain into images of brain captured with respect to ventricular region and images of brain captured with respect to eye ball region. First, the given MRI image of brain is segmented using Particle Swarm Optimization (PSO) algorithm, which is an optimized algorithm for MRI image segmentation. The algorithm proposed in the paper is then applied on the segmented image. The algorithm detects whether the image consist of a ventricular region or an eye ball region and classifies it accordingly.