Fundamental study on preliminary image processing at time development of CNN using chest radiography

Daisuke Hirahara, Emi Yuda, Taro Takahara, Yasuyuki Kobayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Cancers were discovered in bronchi and lungs, chest radiography is getting important. Some lung diseases affect only specific individuals such as lung cancer, but some diseases are related to infectious diseases such as pulmonary tuberculosis, threatening human health. Chest radiography is most convenient method to protect human health from such threats, such as a censer. In this study, we investigated whether preliminary image processing at the time development of a Convolution Neural Network (CNN) for judging presence or absence of a nodule by chest radiography contributes to improvement in accuracy.

Original languageEnglish
Title of host publication2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages102-104
Number of pages3
ISBN (Electronic)9781728105437
DOIs
Publication statusPublished - 2019 Mar
Externally publishedYes
Event1st IEEE Global Conference on Life Sciences and Technologies, LifeTech 2019 - Osaka, Japan
Duration: 2019 Mar 122019 Mar 14

Publication series

Name2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019

Conference

Conference1st IEEE Global Conference on Life Sciences and Technologies, LifeTech 2019
CountryJapan
CityOsaka
Period19/3/1219/3/14

Keywords

  • Chest Radiography
  • Convolution Neural Network
  • Image Processing
  • Lung Cancer
  • Pulmonary Tuberculosis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Health Informatics
  • Neuroscience (miscellaneous)
  • Computer Science Applications
  • Biomedical Engineering

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