Literature DB >> 25981309

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

Feng Li1.   

Abstract

This review paper is based on our research experience in the past 30 years. The importance of radiologists' role is discussed in the development or evaluation of new medical images and of computer-aided detection (CAD) schemes in chest radiology. The four main topics include (1) introducing what diseases can be included in a research database for different imaging techniques or CAD systems and what imaging database can be built by radiologists, (2) understanding how radiologists' subjective judgment can be combined with technical objective features to improve CAD performance, (3) sharing our experience in the design of successful observer performance studies, and (4) finally, discussing whether the new images and CAD systems can improve radiologists' diagnostic ability in chest radiology. In conclusion, advanced imaging techniques and detection/classification of CAD systems have a potential clinical impact on improvement of radiologists' diagnostic ability, for both the detection and the differential diagnosis of various lung diseases, in chest radiology.

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Mesh:

Year:  2015        PMID: 25981309     DOI: 10.1007/s12194-015-0319-0

Source DB:  PubMed          Journal:  Radiol Phys Technol        ISSN: 1865-0333


  62 in total

1.  Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: evaluation with receiver operating characteristic analysis.

Authors:  Yuichi Matsuki; Katsumi Nakamura; Hideyuki Watanabe; Takatoshi Aoki; Hajime Nakata; Shigehiko Katsuragawa; Kunio Doi
Journal:  AJR Am J Roentgenol       Date:  2002-03       Impact factor: 3.959

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

Authors:  Hiroyuki Abe; Heber MacMahon; Roger Engelmann; Qiang Li; Junji Shiraishi; Shigehiko Katsuragawa; Masahito Aoyama; Takayuki Ishida; Kazuto Ashizawa; Charles E Metz; Kunio Doi
Journal:  Radiographics       Date:  2003 Jan-Feb       Impact factor: 5.333

3.  Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.

Authors:  Kenji Suzuki; Feng Li; Shusuke Sone; Kunio Doi
Journal:  IEEE Trans Med Imaging       Date:  2005-09       Impact factor: 10.048

Review 4.  Current status and future potential of computer-aided diagnosis in medical imaging.

Authors:  K Doi
Journal:  Br J Radiol       Date:  2005       Impact factor: 3.039

5.  Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier.

Authors:  Qiang Li; Feng Li; Kunio Doi
Journal:  Acad Radiol       Date:  2008-02       Impact factor: 3.173

6.  Subjective similarity of patterns of diffuse interstitial lung disease on thin-section CT: an observer performance study.

Authors:  Feng Li; Seiji Kumazawa; Junji Shiraishi; Qiang Li; Roger Engelmann; Philip Caligiuri; Heber MacMahon; Kunio Doi
Journal:  Acad Radiol       Date:  2009-04       Impact factor: 3.173

7.  Small lung cancers: improved detection by use of bone suppression imaging--comparison with dual-energy subtraction chest radiography.

Authors:  Feng Li; Roger Engelmann; Lorenzo L Pesce; Kunio Doi; Charles E Metz; Heber Macmahon
Journal:  Radiology       Date:  2011-09-23       Impact factor: 11.105

8.  Digital radiography of subtle pulmonary abnormalities: an ROC study of the effect of pixel size on observer performance.

Authors:  H MacMahon; C J Vyborny; C E Metz; K Doi; V Sabeti; S L Solomon
Journal:  Radiology       Date:  1986-01       Impact factor: 11.105

9.  Computer-aided diagnosis in chest radiography. Preliminary experience.

Authors:  K Abe; K Doi; H MacMahon; M L Giger; H Jia; X Chen; A Kano; T Yanagisawa
Journal:  Invest Radiol       Date:  1993-11       Impact factor: 6.016

10.  Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT.

Authors:  Feng Li; Qiang Li; Roger Engelmann; Masahito Aoyama; Shusuke Sone; Heber MacMahon; Kunio Doi
Journal:  Acad Radiol       Date:  2006-08       Impact factor: 3.173

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  1 in total

Review 1.  Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

Authors:  Ruben T H M Larue; Gilles Defraene; Dirk De Ruysscher; Philippe Lambin; Wouter van Elmpt
Journal:  Br J Radiol       Date:  2016-12-12       Impact factor: 3.039

  1 in total

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