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.