Medical Image Acquisition and Processing: Clinical Validation


The validation of medical imaging (processing and acquisition) can be achieved in multiple ways, somewhat influenced by the context. There are three traps to avoid: First reliance on ground truth requires the knowledge of it before the end of the trial, second comparison to gold standards cannot show improvement and finally one needs to deal with confirmation bias. In this paper we discuss those topics and alternative validation schemes.

Share and Cite:

Goris, M. (2014) Medical Image Acquisition and Processing: Clinical Validation. Open Journal of Medical Imaging, 4, 205-209. doi: 10.4236/ojmi.2014.44028.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Hanley, J.A. and McNeil, B.J. (1982) The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve. Radiology, 143, 29-36.
[2] Berry, D.A., Cronin, K.A., Plevritis, S.K., Fryback, D.G., Clark, L.C., Zelen, M., Mandelblatt, J.S., Yakovlev, A.Y., Habbema, J.D.F. and Feuer, E.J. (2005) Contributions of Screening and Adjuvant Treatment to Reduction in Breast Cancer Mortality in the US from 1975 to 2000. New England Journal of Medicine, 353, 1784-1792.
[3] Zhu, H.J. and Halkar, P.K. (2007) An Evaluation of the Predictive Value of During Treatment 18F-Fluorodeoxyglucose PET/CT Scans in Pediatric Lymphomas. RSNA Scientific Assembly and Annual Meeting Program, 954.
[4] Zhu, H.J., Halkar, R., Alavi, A. and Goris, M.L. (2013) An Evaluation of the Predictive Value of Mid-Treatment 18F-FDG PET/CT Scans in Pediatric Lymphomas and Undefined Criteria of Abnormality in Quantitative Analysis. Hellenic Journal of Nuclear Medicine, 16, 169-74.
[5] Goris, M.L., Bretille, J., Askienazy, S., Purcell, G.P. and Savelli, V. (1989) The Validation of Diagnostic Procedures on Stratified Populations: Application on the Quantification of Thallium Myocardial Perfusion Scintigraphy. American Journal of Physiological Imaging, 4, 11-15.
[6] Diamond, G.A., Rozanski, A., Forrester, J.S., Morris, D., Pollock, B.H., Staniloff, H.M., Berman, D.S. and Swan, H.J.C. (1986) A Model for Assessing the Sensitivity and Specificity of Tests Subject to Selection Bias: Application to Exercise Radionuclide Ventriculography for Diagnosis of Coronary Artery Disease. Journal of Chronic Diseases, 39, 343-355.
[7] Goris, M.L., Zhu, H.J., Blankenberg, F., Chan, F. and Robinson, T.E. (2003) An Automated Approach to Quantitative Air Trapping Measurements in Mild Cystic Fibrosis. Chest, 123, 1655-1663.
[8] Robinson, T.E., Goris, M.L., Zhu, H.J., Chen, X., Bhise, P., Sheikh, F. and Moss, R.B. (2005) Dornase Alfa Reduces Air Trapping in Children with Mild Cystic Fibrosis Lung Disease: A Quantitative Analysis. Chest, 128, 2327-2335.
[9] Hachamovitch, R., Berman, D.S., Shaw, L.J., Kiat, H., Cohen, I., Cabico, J.A., Friedman, J. and Diamond, G.A. (1998) Incremental Prognostic Value of Myocardial Perfusion Single Photon Emission Computed Tomography for the Prediction of Cardiac Death: Differential Stratification for Risk of Cardiac Death and Myocardial Infarction. Circulation, 97, 535-543.
[10] Beinfeld, M.T., Wittenberg, E. and Gazelle, S.G. (2005) Cost-Effectiveness of Whole-Body CT Screening. Radiology, 234, 415-422.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.