ADHD classification using bag of words approach on network features

Berkan Solmaz; Soumyabrata Dey; A. Ravishankar Rao; Mubarak Shah

doi:10.1117/12.911598

24 February 2012 ADHD classification using bag of words approach on network features

Berkan Solmaz, Soumyabrata Dey, A. Ravishankar Rao, Mubarak Shah

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83144T (2012) https://doi.org/10.1117/12.911598
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.

Citation Download Citation

Berkan Solmaz, Soumyabrata Dey, A. Ravishankar Rao, and Mubarak Shah "ADHD classification using bag of words approach on network features", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83144T (24 February 2012); https://doi.org/10.1117/12.911598

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available