Deep feature learning for pulmonary nodule classification in a lung CT

In this paper, we propose a novel method of identifying pulmonary nodules in a lung CT. Specifically, we devise a deep neural network by which we extract abstract information inherent in raw hand-crafted imaging features. We then combine the deep learned representations with the original raw imaging...

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Bibliographic Details

Published in:	2016 4th International Winter Conference on Brain-Computer Interface (BCI) pp. 1 - 3
Main Authors:	Bum-Chae Kim, Yu Sub Sung, Heung-Il Suk
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.02.2016
Subjects:	Cancer Computed tomography Deep learning Feature extraction Lung cancer Lungs Noise reduction Pulmonary nodule classification Stacked denoising autoencoder Training
ISBN:	1467378410, 9781467378413
Online Access:	Get full text
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