Short Course on Image Quality and Statistical Analysis
We are planning a future IEEE NSS/MIC short course on Image Quality and Statistical Analysis. This course will cover probability and statistics as applied in a variety of imaging applications. We will start with a review of fundamental material needed for this course including the basic definitions of probability and the many random factors in imaging. We will then cover advanced estimation methods, detector statistics, and statistical image reconstruction at a level that will enable attendees to better understand the state-of-the-art presented in the literature. Special attention will be given to Bayesian estimation and reconstruction methods and comparisons of these methods to non-Bayesian approaches. The very basics of Monte Carlo methods will be presented to introduce the attendees to the terminology. These discussions will culminate in lectures on the statistical nature of image quality and how to define image quality using task performance. ROC analysis and ROC variants will be discussed. Finally, we will end by covering some common pitfalls that arise when computing image quality measures and also discuss the limitations and utility of traditional hypothesis testing methods.
Stay tuned for more information about this course
Books and Book Chapters
Foundations of Image Science
Harrison H. Barrett and Kyle J. Myers
Small-Animal Spect Imaging
Matthew A. Kupinski, editor
The Handbook of Medical Image Perception and Techniques
Ehsan Samei and Elizabeth Krupinski, Editors
Chapter: Implementation of Observer Models
Matthew A. Kupinski
Photon Counting: Fundamentals and Applications
Nikolay Briton and Anton Nikiforov, Editors
Chapter 5: Computational Methods for Photon-Counting and Photon-Processing Detectors
Gathering further information. More chapters and review articles to come...