Song, Y., Cai, W., Huang, H., Wang, X., Zhou, Y., Fulham, M. and Feng, D. (2014) Lesion Detection and Characterization with Context Driven Approximation in Thoracic FDG PET-CT Images of NSCLC Studies. IEEE Trans. Med Imag, 33, 408- 421. https://doi.org/10.1109/TMI.2013.2285931

has been cited by the following article:

• 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.