Literature DB >> 12533660

Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies.

Hiroyuki Abe1, Heber MacMahon, Roger Engelmann, Qiang Li, Junji Shiraishi, Shigehiko Katsuragawa, Masahito Aoyama, Takayuki Ishida, Kazuto Ashizawa, Charles E Metz, Kunio Doi.   

Abstract

Since 1996, computer-aided diagnosis (CAD) schemes have been presented as interactive demonstrations on computer workstations at each scientific assembly of the Radiological Society of North America. The schemes involved (a) detection of pulmonary nodules, (b) temporal subtraction, (c) detection of interstitial lung disease, (d) differential diagnosis of interstitial lung disease, and (e) distinction between benign and malignant pulmonary nodules on chest radiographs. Large-scale observer tests were carried out to examine how radiologists can benefit from CAD systems. Observer performance was evaluated by analysis of receiver operating characteristic (ROC) curves. The statistical significance of the difference between the areas under the ROC curves without and with CAD was analyzed with the Student t test. In all of the tests, the diagnostic accuracy of the radiologists in total improved significantly when CAD was used. This result provides additional evidence that CAD has the potential to improve the performance of radiologists in their decision-making process in interpreting chest radiographs. Copyright RSNA, 2003.

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Year:  2003        PMID: 12533660     DOI: 10.1148/rg.231025129

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  12 in total

1.  Computer-assisted detection of pulmonary nodules: preliminary observations using a prototype system with multidetector-row CT data sets.

Authors:  Leo P Lawler; Susan A Wood; Harpreet K Pannu; Elliot K Fishman; Harpreet S Pannu
Journal:  J Digit Imaging       Date:  2003-12-15       Impact factor: 4.056

2.  Computer-aided diagnosis for contrast-enhanced ultrasound in the liver.

Authors:  Katsutoshi Sugimoto; Junji Shiraishi; Fuminori Moriyasu; Kunio Doi
Journal:  World J Radiol       Date:  2010-06-28

Review 3.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

4.  Effect of multiscale processing in digital chest radiography on automated detection of lung nodule with a computer assistance system.

Authors:  Qian He; Wen He; Keyang Wang; Daqing Ma
Journal:  J Digit Imaging       Date:  2008-02-01       Impact factor: 4.056

5.  Machine Learning in Computer-aided Diagnosis of the Thorax and Colon in CT: A Survey.

Authors:  Kenji Suzuki
Journal:  IEICE Trans Inf Syst       Date:  2013-04-01

Review 6.  Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

Authors:  Feng Li
Journal:  Radiol Phys Technol       Date:  2015-05-17

7.  Computer-assisted diagnosis of tuberculosis: a first order statistical approach to chest radiograph.

Authors:  Jen Hong Tan; U Rajendra Acharya; Collin Tan; K Thomas Abraham; Choo Min Lim
Journal:  J Med Syst       Date:  2011-07-07       Impact factor: 4.460

8.  Black box integration of computer-aided diagnosis into PACS deserves a second chance: results of a usability study concerning bone age assessment.

Authors:  Ina Geldermann; Christoph Grouls; Christiane Kuhl; Thomas M Deserno; Cord Spreckelsen
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

9.  Feature Reduction in Graph Analysis.

Authors:  Rapepun Piriyakul; Punpiti Piamsa-Nga
Journal:  Sensors (Basel)       Date:  2008-08-19       Impact factor: 3.576

10.  Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

Authors:  Adrien Depeursinge; Alejandro Vargas; Frédéric Gaillard; Alexandra Platon; Antoine Geissbuhler; Pierre-Alexandre Poletti; Henning Müller
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-06-01       Impact factor: 2.924

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