Computer-Aided Detection of Lung Nodules in Chest X-Rays using Deep Convolutional Neural Networks

Murat UÇAR; Emine UÇAR

doi:https://doi.org/10.35377/saucis.02.01.538249

Article Details

Computer-Aided Detection of Lung Nodules in Chest X-Rays using Deep Convolutional Neural Networks

Authors:

Murat UÇAR | Emine UÇAR

Main Topics:

Data processing and computer science

Journal:

Sakarya University Journal of Computer and Information Sciences 2019 Vol.2 Issue 1, pp.1-8

Document Type:

Article

Publication Date:

4/2019

Document Language:

English

Document ID (Org No.):

2000552136

DOI:

https://doi.org/10.35377/saucis.02.01.538249

Abstract:

 

Chest X-Rays are most accessible medical imaging
technique for diagnosing abnormalities in the heart and lung area.
Automatically detecting these abnormalities with high accuracy could greatly
enhance real world diagnosis processes. In this study we aim to improve the
accuracy of convolutional deep learning by using Laplacian of Gaussian
filtering. In this study, we have used the publicly available Japanese Society
of Radiological Technology dataset including 247 radiograms. For improving the
performance of convolutional neural networks we used LoG filter and also we
used an advanced version of AlexNet and GoogleNet to compare our results. The
results indicated that, convolutional neural network with Laplacian of Gaussian
filter model produced the best results with 82.43% accuracy. Convolutional
neural network with Laplacian of Gaussian filter model is followed by convolutional
neural network with an accuracy of 72.97%, followed by GoogleNet model with an
accuracy of 68.92%. Out of the four model types utilized, the AlexNet model
produced the lowest accuracy with a value of 64.86%. The results obtained here
demonstrate that the pre-processing technique like Laplacian of Gaussian filter
can improve the accuracy.

Article Details

Computer-Aided Detection of Lung Nodules in Chest X-Rays using Deep Convolutional Neural Networks

Authors: Murat UÇAR | Emine UÇAR

Main Topics: Data processing and computer science

Journal: Sakarya University Journal of Computer and Information Sciences 2019 Vol.2 Issue 1, pp.1-8

Document Type: Article

Publication Date: 4/2019

Document Language: English

Document ID (Org No.): 2000552136

DOI: https://doi.org/10.35377/saucis.02.01.538249

Issues

Authors:

Murat UÇAR | Emine UÇAR

Main Topics:

Data processing and computer science

Journal:

Sakarya University Journal of Computer and Information Sciences 2019 Vol.2 Issue 1, pp.1-8

Document Type:

Article

Publication Date:

4/2019

Document Language:

English

Document ID (Org No.):

2000552136

DOI:

https://doi.org/10.35377/saucis.02.01.538249