A four-alternative forced choice (4AFC) software for observer performance evaluation in radiology

Guozhi Zhang; Lesley Cockmartin; Hilde Bosmans

doi:10.1117/12.2216386

24 March 2016 A four-alternative forced choice (4AFC) software for observer performance evaluation in radiology

Guozhi Zhang, Lesley Cockmartin, Hilde Bosmans

Proceedings Volume 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment; 97871E (2016) https://doi.org/10.1117/12.2216386
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Four-alternative forced choice (4AFC) test is a psychophysical method that can be adopted for observer performance evaluation in radiological studies. While the concept of this method is well established, difficulties to handle large image data, perform unbiased sampling, and keep track of the choice made by the observer have restricted its application in practice. In this work, we propose an easy-to-use software that can help perform 4AFC tests with DICOM images. The software suits for any experimental design that follows the 4AFC approach. It has a powerful image viewing system that favorably simulates the clinical reading environment. The graphical interface allows the observer to adjust various viewing parameters and perform the selection with very simple operations. The sampling process involved in 4AFC as well as the speed and accuracy of the choice made by the observer is precisely monitored in the background and can be easily exported for test analysis. The software has also a defensive mechanism for data management and operation control that minimizes the possibility of mistakes from user during the test. This software can largely facilitate the use of 4AFC approach in radiological observer studies and is expected to have widespread applicability.

Citation Download Citation

Guozhi Zhang, Lesley Cockmartin, and Hilde Bosmans "A four-alternative forced choice (4AFC) software for observer performance evaluation in radiology", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97871E (24 March 2016); https://doi.org/10.1117/12.2216386

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