Observer Performance Methods For Diagnostic Imaging

Gives an accessible overview of R programming for medical imaging and the methods of observer performance testing. Explains the fundamental statistical concepts. Reinforces learning using worked problems and R software code, in addition to examples that utilize standalone ROC software. Starts with basic ROC analysis and builds to extensions of ROC methods for solving more complex but clinically realistic tasks. Emphasizes psychophysical models of observer performance (e.g., binormal model, contaminated binormal model, proper ROC model), and demonstrates how they can give better results than from purely statistical approaches. Supplementary tools and materials available at: www.devchakraborty.com; www.expertcadanalytics.com.

Includes Proceedings Vol. 7821

Includes Proceedings Vol. 7821