Literature DB >> 19604661

Computer-aided diagnosis in chest radiography: beyond nodules.

Bram van Ginneken1, Laurens Hogeweg, Mathias Prokop.   

Abstract

Chest radiographs are the most common exam in radiology. They are essential for the management of various diseases associated with high mortality and morbidity and display a wide range of findings, many of them subtle. In this survey we identify a number of areas beyond pulmonary nodules that could benefit from computer-aided detection and diagnosis (CAD) in chest radiography. These include interstitial infiltrates, catheter tip detection, size measurements, detection of pneumothorax and detection and quantification of emphysema. Recent work in these areas is surveyed, but we conclude that the amount of research devoted to these topics is modest. Reasons for the slow pace of CAD development in chest radiography beyond nodules are discussed.

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Year:  2009        PMID: 19604661     DOI: 10.1016/j.ejrad.2009.05.061

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  21 in total

1.  Evaluation of computer-aided detection and diagnosis systems.

Authors:  Nicholas Petrick; Berkman Sahiner; Samuel G Armato; Alberto Bert; Loredana Correale; Silvia Delsanto; Matthew T Freedman; David Fryd; David Gur; Lubomir Hadjiiski; Zhimin Huo; Yulei Jiang; Lia Morra; Sophie Paquerault; Vikas Raykar; Frank Samuelson; Ronald M Summers; Georgia Tourassi; Hiroyuki Yoshida; Bin Zheng; Chuan Zhou; Heang-Ping Chan
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

2.  Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs.

Authors:  Szilárd Vajda; Alexandros Karargyris; Stefan Jaeger; K C Santosh; Sema Candemir; Zhiyun Xue; Sameer Antani; George Thoma
Journal:  J Med Syst       Date:  2018-06-29       Impact factor: 4.460

Review 3.  Computer-aided Assessment of Catheters and Tubes on Radiographs: How Good Is Artificial Intelligence for Assessment?

Authors:  Xin Yi; Scott J Adams; Robert D E Henderson; Paul Babyn
Journal:  Radiol Artif Intell       Date:  2020-01-29

4.  EMPHYSEMA QUANTIFICATION IN A MULTI-SCANNER HRCT COHORT USING LOCAL INTENSITY DISTRIBUTIONS.

Authors:  C S Mendoza; G R Washko; J C Ross; A A Diaz; D A Lynch; J D Crapo; E K Silverman; B Acha; C Serrano; R San José Estépar
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2012

5.  Automatic tissue characterization of air trapping in chest radiographs using deep neural networks.

Authors:  Awais Mansoor; Geovanny Perez; Gustavo Nino; Marius George Linguraru
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

Review 6.  Computer-assisted detection of infectious lung diseases: a review.

Authors:  Ulaş Bağcı; Mike Bray; Jesus Caban; Jianhua Yao; Daniel J Mollura
Journal:  Comput Med Imaging Graph       Date:  2011-07-01       Impact factor: 4.790

7.  Combination of texture and shape features to detect pulmonary abnormalities in digital chest X-rays.

Authors:  Alexandros Karargyris; Jenifer Siegelman; Dimitris Tzortzis; Stefan Jaeger; Sema Candemir; Zhiyun Xue; K C Santosh; Szilárd Vajda; Sameer Antani; Les Folio; George R Thoma
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-06-20       Impact factor: 2.924

8.  Edge map analysis in chest X-rays for automatic pulmonary abnormality screening.

Authors:  K C Santosh; Szilárd Vajda; Sameer Antani; George R Thoma
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-03-19       Impact factor: 2.924

9.  Modified Chrispin-Norman chest radiography score for cystic fibrosis: observer agreement and correlation with lung function.

Authors:  P A de Jong; J A Achterberg; O A M Kessels; B van Ginneken; L Hogeweg; F J Beek; S W J Terheggen-Lagro
Journal:  Eur Radiol       Date:  2010-10-06       Impact factor: 5.315

10.  Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

Authors:  Anna H van't Hoog; Helen K Meme; Kayla F Laserson; Janet A Agaya; Benson G Muchiri; Willie A Githui; Lazarus O Odeny; Barbara J Marston; Martien W Borgdorff
Journal:  PLoS One       Date:  2012-07-06       Impact factor: 3.240

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