Relevance of statistically significant differences between reconstruction algorithms
- 1 March 1996
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 5 (3) , 554-556
- https://doi.org/10.1109/83.491331
Abstract
When comparing reconstruction algorithms, differences in figures of performance merit that are too small to be of any practical relevance may still be statistically significant. We formalize the notion of "relevance" and propose an evaluation methodology in which statistical significance is retained for relevant improvements, but not for irrelevant ones.Keywords
This publication has 9 references indexed in Scilit:
- Efficient 3D grids for image reconstruction using spherically-symmetric volume elementsIEEE Transactions on Nuclear Science, 1995
- A methodology for testing for statistically significant differences between fully 3D PET reconstruction algorithmsPhysics in Medicine & Biology, 1994
- Evaluation of task-oriented performance of several fully 3D PET reconstruction algorithmsPhysics in Medicine & Biology, 1994
- Algebraic reconstruction techniques can be made computationally efficient (positron emission tomography application)IEEE Transactions on Medical Imaging, 1993
- Evaluation of statistical methods of image reconstruction through ROC analysis (emission tomography)IEEE Transactions on Medical Imaging, 1992
- Performance evaluation of an iterative image reconstruction algorithm for positron emission tomographyIEEE Transactions on Medical Imaging, 1991
- Method of evaluating image-recovery algorithms based on task performanceJournal of the Optical Society of America A, 1990
- Evaluators of image reconstruction algorithmsInternational Journal of Imaging Systems and Technology, 1989
- Hotelling trace criterion and its correlation with human-observer performanceJournal of the Optical Society of America A, 1987