Assessment of Morphological Markers from Autistic MRI
B.J. Bipin Nair1, K. Sahith Kumar2
1B.J. Bipin Nair, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
2K. Sahith Kumar, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 01 May 2019 | Manuscript Published on 08 May 2019 | PP: 109-114 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11210275S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Our proposed work we are predicting the earlier stage developmental disorder autism through morphological markers .it can be performed through the analysis of cortical thickness from MRI with various parameter like thickness, gyrification, volume etc. from our work we are considering the MRI data set from the age between 15 to 30 year .in our work we are using various segmentation technique to calculate the various parameters like cortical thickness, gyrification, etc. from brain MRI. Through the parameter we are predicting the autism in the range of age with the experimentation of morphological markers.
Keywords: ASD -Autism Spectrum Disorder, MRI, Voxel Based Morphometry-VBM, Gray Matter-GA, White Matter-WM.
Scope of the Article: Component-Based Software Engineering