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2018 | OriginalPaper | Chapter

Effects of Preprocessing in Slice-Level Classification of Interstitial Lung Disease Based on Deep Convolutional Networks

Authors : Yongjun Chang, Örjan Smedby

Published in: VipIMAGE 2017

Publisher: Springer International Publishing

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Abstract

Several preprocessing methods are applied to the automatic classification of interstitial lung disease (ILD). The proposed methods are used for the inputs to an established convolutional neural network in order to investigate the effect of those preprocessing techniques to slice-level classification accuracy. Experimental results demonstrate that the proposed preprocessing methods and a deep learning approach outperformed the case of the original images input to deep learning without preprocessing.

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previous chapter Radiomics-Based Recognition of Metastatic and Histopathological Patterns of Lung Cancer
next chapter Automated Assessment of Hallux Valgus in Radiographic Images
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Metadata
Title
Effects of Preprocessing in Slice-Level Classification of Interstitial Lung Disease Based on Deep Convolutional Networks
Authors
Yongjun Chang
Örjan Smedby
Copyright Year
2018
Book
VipIMAGE 2017

Print ISBN: 978-3-319-68194-8

Electronic ISBN: 978-3-319-68195-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-68195-5_67