Classification of CT Scan Images of Lungs Using Deep Convolutional Neural Network with External Shape-Based Features.

Abstract:

:In this paper, a simplified yet efficient architecture of a deep convolutional neural network is presented for lung image classification. The images used for classification are computed tomography (CT) scan images obtained from two scientifically used databases available publicly. Six external shape-based features, viz. solidity, circularity, discrete Fourier transform of radial length (RL) function, histogram of oriented gradient (HOG), moment, and histogram of active contour image, have also been identified and embedded into the proposed convolutional neural network. The performance is measured in terms of average recall and average precision values and compared with six similar methods for biomedical image classification. The average precision obtained for the proposed system is found to be 95.26% and the average recall value is found to be 69.56% in average for the two databases.

journal_name

J Digit Imaging

authors

Srivastava V,Purwar RK

doi

10.1007/s10278-019-00245-9

subject

Has Abstract

pub_date

2020-02-01 00:00:00

pages

252-261

issue

1

eissn

0897-1889

issn

1618-727X

pii

10.1007/s10278-019-00245-9

journal_volume

33

pub_type

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