automatic detection of adhd subjects using deep convolutional neural network

Automatic Detection of ADHD subjects using Deep Convolutional Neural Network

Arjun Watane, Soumyabrata Dey(arjunwatane@knights.ucf.edu, soumyabrata.dey@gmail.com)

University of Central Florida

I. Problem & Motivation:

Automatic detection of ADHDStructural MRI

Strict 3-D anatomical structure

Lack of biological measures for diagnosis Subjective to Verbal Test Inconsistent and over-diagnosis problem

Data set: NYU data center of ADHD-200 203 training, 41 test subjects

Network Configurations

Input Blob – 203 Subjects, 21 slices per subject, 256x256 pixels slice image

Layer – convolution and max-pooling to generate feature map

5 convolution layers, 4 max pooling layers, 2 fully connected layers (FC)

Extraction of features using pretrained Imagenet model

III. Formulation: Slice 1

Slice 2

Slice n

Combine FC6 and FC7 for each slice

Vector Length = 4096x2 = 8192

SVM Classifier

Slice 1 Decision

Convolutional Neural Network

Extraction of Feature Layer FC6 and FC7

Slice 2 Decision

Slice n Decision

Slices

Type SliceAccuracyFC6 %

Accuracy FC7 %

Accuracy FC6 and FC7 %

1 GM 75 65.85 63.42 78.05

2 Normal 55 70.73 51.22 78.05

3 WM 55 46.34 60.98 78.05

4 NGW 195 63.41 65.85 70.73

5GM (Late

Fusion) 75, 85, 115 75.61 78.05 80.49

Late Fusion of FC6 and FC7 features showed the highest accuracy of ADHD classification, at 80.49%.

V. Visualization of Features :

Gray Matter

White Matter

Normalized

Slices

1 2 3 4 50

10

20

30

40

50

60

70

80

90

IV. Image Pre-Processing :

VI. Results :

Accuracy Comparison of Independent Feature vs. Feature Combination

Brain Segmentation

Convolution 1 Convolution 2 Convolution 3 Convolution 4 Convolution 5

FC6+FC7

FC7

FC6

Weighted Late Fusion

DW .TfinalD

:finalD Final decision

:W Weight vector

:D Decision vector

,2

,2

1

)2(

2

ni

ni

ie

e

S

02 ni

02 ni

''2

'1

' ,...,, nwwwW : Calculated from training data

,'iii wSw

2ni 0

1

II. Convolutional Neural Network :

FC6 FC72048 2048

nwww ,...,, 21W

},...,2,1{ ni

Slices are ranked based on the score. Slice1 has highest weight'iw