Employing Thresholding and Sobel Technique to Detect Autism from MRI
B.J. Bipin Nair1, Navaneeth Vijayan2
1B.J. Bipin Nair, Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
2Navaneeth Vijayan, 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: 99-103 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11190275S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In our proposed work we are doing various Segmentation methods to detect the autistic disorders using cerebral brain MRI. In this work we are collecting brain MRI image for autistic disorders and uses an efficient pre-processing technique to remove the noise from brain MRI, then for locating the damaged tissue from brain MRI we are using an efficient segmentation techniques like thresholding and sobel to extract the affected region, then proceeds with checking how efficiently we are detecting the affected region.
Keywords: ABIDE, MRI, Sobel Edge Detection, Digital Image Processing (DIP).
Scope of the Article: Routing, Switching and Addressing Techniques