Diagnosis and Inference of ADHD
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 7
Abstract
Attention Deficit Hyperactivity Disorder (ADHD) may occur due to abnormal brain development or Brain injuries occurring before, during or after birth. Any brain damage or brain injury may cause abnormality in the growth of caudate nucleus and other brain parts. The children with ADHD may have caudate volume reduction. So, in this paper, to predict the prevalence of ADHD, three different segmentation techniques namely Fuzzy CMeans Segmentation, Region Based Active Contour Segmentation and Threshold Based Segmentation are proposed to extract the caudate nucleus from the MRI brain images. The segmentation results are compared and analyzed based on various performance metrics and found that the Fuzzy C-Means Segmentation algorithm performs well in terms of region continuity, computation time, and accuracy. Instead of going for medication or any other behavioral treatment the brain imaging techniques may easily identify the occurrence of ADHD and assist the neurologists to learn more about this disorder and hence take preventive measures to overcome this problem.
Authors and Affiliations
I. Jemima Bibiyana, K. Krishnaveni, E. Radhamani
Keywords
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