Literature DB >> 6862810

The effect of verification on the assessment of imaging techniques.

G Revesz, H L Kundel, M Bonitatibus.   

Abstract

In order to measure the accuracy of a diagnostic imaging technique, the correctness of each observer decision must be determined. This is often difficult in clinical cases, and various strategies are frequently used to approximate the truth. Experiments using chest radiographs as an example are reported to show the pitfalls in those strategies. To assess relative accuracies of three different radiographic techniques, chest radiographs were taken of 66 patients with each of the three techniques, and the films were evaluated by six radiologists. Their findings were then scored by comparing them with the correct decision defined by each of the following methods: majority vote, consensus opinion, expert judgment, feedback review, and clinical/pathologic proof. The findings showed that any one of the techniques could be shown to be better than the other, depending on how the truth was defined. It is concluded, therefore, that strategies that define the presence or absence of disease only by the diagnostic tests under evaluation are inadequate. The truth must be determined by clinical or pathologic proof and follow-up data.

Entities:  

Mesh:

Year:  1983        PMID: 6862810     DOI: 10.1097/00004424-198303000-00018

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  10 in total

Review 1.  ROC analysis in medical imaging: a tutorial review of the literature.

Authors:  Charles E Metz
Journal:  Radiol Phys Technol       Date:  2007-10-27

2.  Some methodological questions concerning receiver operating characteristic (ROC) analysis as a method for assessing image quality in radiology.

Authors:  M B Harrington
Journal:  J Digit Imaging       Date:  1990-11       Impact factor: 4.056

3.  LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned.

Authors:  Samuel G Armato; Lubomir Hadjiiski; Georgia D Tourassi; Karen Drukker; Maryellen L Giger; Feng Li; George Redmond; Keyvan Farahani; Justin S Kirby; Laurence P Clarke
Journal:  J Med Imaging (Bellingham)       Date:  2015-04

4.  The Lung Image Database Consortium (LIDC): ensuring the integrity of expert-defined "truth".

Authors:  Samuel G Armato; Rachael Y Roberts; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Geoffrey McLennan; Roger M Engelmann; Peyton H Bland; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

5.  The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans.

Authors:  Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; Charles R Meyer; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Eric A Hoffman; Claudia I Henschke; Rachael Y Roberts; Matthew S Brown; Roger M Engelmann; Richard C Pais; Christopher W Piker; David Qing; Masha Kocherginsky; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-11       Impact factor: 3.173

6.  PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images.

Authors:  Samuel G Armato; Henkjan Huisman; Karen Drukker; Lubomir Hadjiiski; Justin S Kirby; Nicholas Petrick; George Redmond; Maryellen L Giger; Kenny Cha; Artem Mamonov; Jayashree Kalpathy-Cramer; Keyvan Farahani
Journal:  J Med Imaging (Bellingham)       Date:  2018-11-10

7.  LUNGx Challenge for computerized lung nodule classification.

Authors:  Samuel G Armato; Karen Drukker; Feng Li; Lubomir Hadjiiski; Georgia D Tourassi; Roger M Engelmann; Maryellen L Giger; George Redmond; Keyvan Farahani; Justin S Kirby; Laurence P Clarke
Journal:  J Med Imaging (Bellingham)       Date:  2016-12-19

8.  Malformations of cortical development: diagnostic accuracy of fetal MR imaging.

Authors:  Orit A Glenn; Addison A Cuneo; A James Barkovich; Zary Hashemi; Agnes I Bartha; Duan Xu
Journal:  Radiology       Date:  2012-04-10       Impact factor: 11.105

9.  Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski; Philip N Cascade; Ella A Kazerooni; Aamer R Chughtai; Chad Poopat; Thomas Song; Luba Frank; Jadranka Stojanovska; Anil Attili
Journal:  Acad Radiol       Date:  2009-12       Impact factor: 3.173

10.  Assessment of radiologist performance in the detection of lung nodules: dependence on the definition of "truth".

Authors:  Samuel G Armato; Rachael Y Roberts; Masha Kocherginsky; Denise R Aberle; Ella A Kazerooni; Heber Macmahon; Edwin J R van Beek; David Yankelevitz; Geoffrey McLennan; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Philip Caligiuri; Leslie E Quint; Baskaran Sundaram; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2009-01       Impact factor: 3.173

  10 in total

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