Cargando…
Computer-aided detection in chest radiography based on artificial intelligence: a survey
As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applicati...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103992/ https://www.ncbi.nlm.nih.gov/pubmed/30134902 http://dx.doi.org/10.1186/s12938-018-0544-y |
_version_ | 1783349400909643776 |
---|---|
author | Qin, Chunli Yao, Demin Shi, Yonghong Song, Zhijian |
author_facet | Qin, Chunli Yao, Demin Shi, Yonghong Song, Zhijian |
author_sort | Qin, Chunli |
collection | PubMed |
description | As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applications, the study conducts a comprehensive survey on computer-aided detection (CAD) systems, and especially focuses on the artificial intelligence technology applied in chest radiography. The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography. Then, the CAD system in the detection of specific disease (pulmonary nodules, tuberculosis, and interstitial lung diseases) and multiple diseases is described, focusing on the basic principles of the algorithm, the data used in the study, the evaluation measures, and the results. Finally, the paper summarizes the CAD system in chest radiography based on artificial intelligence and discusses the existing problems and trends. |
format | Online Article Text |
id | pubmed-6103992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61039922018-08-30 Computer-aided detection in chest radiography based on artificial intelligence: a survey Qin, Chunli Yao, Demin Shi, Yonghong Song, Zhijian Biomed Eng Online Review As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applications, the study conducts a comprehensive survey on computer-aided detection (CAD) systems, and especially focuses on the artificial intelligence technology applied in chest radiography. The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography. Then, the CAD system in the detection of specific disease (pulmonary nodules, tuberculosis, and interstitial lung diseases) and multiple diseases is described, focusing on the basic principles of the algorithm, the data used in the study, the evaluation measures, and the results. Finally, the paper summarizes the CAD system in chest radiography based on artificial intelligence and discusses the existing problems and trends. BioMed Central 2018-08-22 /pmc/articles/PMC6103992/ /pubmed/30134902 http://dx.doi.org/10.1186/s12938-018-0544-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Qin, Chunli Yao, Demin Shi, Yonghong Song, Zhijian Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title | Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title_full | Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title_fullStr | Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title_full_unstemmed | Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title_short | Computer-aided detection in chest radiography based on artificial intelligence: a survey |
title_sort | computer-aided detection in chest radiography based on artificial intelligence: a survey |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103992/ https://www.ncbi.nlm.nih.gov/pubmed/30134902 http://dx.doi.org/10.1186/s12938-018-0544-y |
work_keys_str_mv | AT qinchunli computeraideddetectioninchestradiographybasedonartificialintelligenceasurvey AT yaodemin computeraideddetectioninchestradiographybasedonartificialintelligenceasurvey AT shiyonghong computeraideddetectioninchestradiographybasedonartificialintelligenceasurvey AT songzhijian computeraideddetectioninchestradiographybasedonartificialintelligenceasurvey |