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Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S. and Darrell, T. (2014) Caffe: Convolutional Architecture for Fast Feature Embedding. ACM Conference on Multimedia, 675-678. https://doi.org/10.1145/2647868.2654889

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• TITLE: A Study on Diagnostic Assist Systems of Chronic Obstructive Pulmonary Disease from Medical Images by Deep Learning

  AUTHORS: Toru Kimura, Takashi Kawakami, Akihiro Kikuchi, Ryosuke Ooev, Masaki Akiyama, Hiroyuki Horikoshi

  KEYWORDS: Deep Learning, CT Images, Diagnostic Assist Systems, Chronic Obstructive Pulmonary Disease

  JOURNAL NAME: Journal of Computer and Communications, Vol.6 No.1, December 29, 2017

  ABSTRACT: In this paper, we propose new diagnostic assist systems of medical images using deep learning algorithms. Specifically, we aim to develop a diagnostic support system for the very early stage of chronic obstructive pulmonary disease (COPD) based on the CT images. It is said that COPD is a disease that develops due to long-term smoking, and it is said that there are a large number of latent onset reserve forces. By discovering this COPD in the very early period 0 and improving the living conditions, subsequent severity can be avoided in many cases, so a system that will help diagnosis by professional radiologists is needed. We show the some experimental results examined by the constructed system.