Identification and Research of Adhd and Healthy Controls using Fmri
K.Thaiyalnayaki
K.Thaiyalnayaki, Department of ECE, Saveetha School of Engineering, SIMATS, Chennai (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 370-372 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10780886S19/19©BEIESP | DOI: 10.35940/ijeat.F1078.0886S19
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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: Analyzing the brain regions for different activations corresponding to the activation input for an experimental setup of task functional MRI or a resting state functional Magnetic Resonance Imaging(fMRI) for a diagnosed or healthy control is a challenging issue as the processing data is voluminous 4D data with nearly 1,51,552 voxels for a single volume of 261 scans fMRI. The data considered for analysis consists of 10 healthy controls and 10 Attention Deficit Hyperactivity Disorder(ADHD) fMRI. The workflow starts with preprocessing the individual scan for realignment, coregistration and Normalisation to Montreal Neurological Institute (MNI) space. Single site scan visit consists of 64x64x37 voxels. Seventy independent components are obtained from processed data by data reduction, Independent Component Analysis (ICA) calculation, Back reconstruction and Component Calibration. ICA performs satisfactorily well on temporal and spatial localization. Visual medial network activation is pronounced in ADHD Controls than in healthy people. Sagittal, Axial and Coronal view of ADHD controls is obtained as component number 42.The analysis is further used for the automatic classification of healthy controls and ADHD people.
Keywords: Controls Research Classification Control.
Scope of the Article: Classification