Efficient way of skull stripping in MRI to detect brain tumor by applying morphological operations, after detection of false background

• Main Authors: Mohsin, Sajjad, Sajjad, Sadaf, Malik, Zeeshan, Abdullah, Abdul Hanan
• Format: Article
• Language: English
• Published: International Association of Computer Science and Information Technology Press (IACSIT Press) 2012
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/31780/2/145-T050.pdf; http://eprints.utm.my/id/eprint/31780/
• Institution: Universiti Teknologi Malaysia

Brain MRI is used to get deeper view of the brain conditions. Skull stripping is a major phase sometimes refers to a pre-process in MRI brain imaging applications which refers to the removal of brain non-cerebral tissues. Various algorithms have been developed to improve the effectiveness of stripping skull from MRI. Morphological algorithms of “Erosion” and “Dilation” are recursively applied together to remove the skull. Besides the removal of skull, “erosion” distorts some cerebral tissues due to the presence of falsebackground. So “Dilation” process is applied for the restoration. In this study, we improved the efficiency of stripping skull in MRI using systematic application of “Erosion” with AOI (Area of Interest) approach after the detection of false-background. Before applying “Erosion”, a false back ground is detected. We identified the skull boundary through Dilation and then used scan line algorithm to fill the false background area. Consequently “Erosion” algorithm will only erode the AOI, resulting in the stripping of skull without any effect on the other tissues of the brain. Results show that the accuracy rate up to 95% is obtained and 43% efficiency is increased as compared to the different morphological techniques used previously.