Presentation 2015-03-16
Feature Analysis for Diffuse Lung Disease with Deep Convolutional Neural Network
Satoshi SUZUKI, Hayaru SHOUNO, Shoji KIDO,
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Abstract(in English) The computer aided diagnosis (CAD) system is desired to develop for supporing physicians to diagnose the diffuse lung diseeases (DLD). In order to devlop the system, we a DLD feature analysis method with deep convolutional neural network (DCNN) for the classification of DLDs. DCNN is a kind of multi layer neural network which can automatically extract features express the input data, however, it requires larage amount of training data. In the field of medical image analysis, the number of acquired data sometimes too few to train the learning system. Thus, we introduce a kind of semi-supervised learning (SSL) method to train the DCNN, that is we apply natural image, which we can easily collect in massive, for the unlabeled data, and the small number of the DLD image as the labeled data. We compare DCNNs with training of i) DLD CT images only, ii) natural images only, and iii) DLC CT images + natural images, and show the result of case iii) would be better DCNN feature rather than those of others.
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Keyword(in English) Deep Convolutional Neural Network / Semi-supervised Learning / Diffuse Lung Disease image analysis
Paper # MBE2014-163,NC2014-114
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Conference Information
Committee NC
Conference Date 2015/3/9(1days)
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Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Feature Analysis for Diffuse Lung Disease with Deep Convolutional Neural Network
Sub Title (in English)
Keyword(1) Deep Convolutional Neural Network
Keyword(2) Semi-supervised Learning
Keyword(3) Diffuse Lung Disease image analysis
1st Author's Name Satoshi SUZUKI
1st Author's Affiliation Deapartment of Informatics and Engineering, University of Electro-Communications()
2nd Author's Name Hayaru SHOUNO
2nd Author's Affiliation Graduate School of Informatics and Engineering, University of Electro-Communications
3rd Author's Name Shoji KIDO
3rd Author's Affiliation Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University
Date 2015-03-16
Paper # MBE2014-163,NC2014-114
Volume (vol) vol.114
Number (no) 515
Page pp.pp.-
#Pages 6
Date of Issue