Back to Search
Start Over
Effects of thresholding on correlation-based image similarity metrics.
- Source :
-
Frontiers in neuroscience [Front Neurosci] 2015 Oct 29; Vol. 9, pp. 418. Date of Electronic Publication: 2015 Oct 29 (Print Publication: 2015). - Publication Year :
- 2015
-
Abstract
- The computation of image similarity is important for a wide range of analyses in neuroimaging, from decoding to meta-analysis. In many cases the images being compared have empty voxels, but the effects of such empty voxels on image similarity metrics are poorly understood. We present a detailed investigation of the influence of different degrees of image thresholding on the outcome of pairwise image comparison. Given a pair of brain maps for which one of the maps is thresholded, we show that an analysis using the intersection of non-zero voxels across images at a threshold of Z = ±1.0 maximizes accuracy for retrieval of a list of maps of the same contrast, and thresholding up to Z = ±2.0 can increase accuracy as compared to comparison using unthresholded maps. Finally, maps can be thresholded up to to Z = ±3.0 (corresponding to 25% of voxels non-empty within a standard brain mask) and still maintain a lower bound of 90% accuracy. Our results suggest that a small degree of thresholding may improve the accuracy of image similarity computations, and that robust meta-analytic image similarity comparisons can be obtained using thresholded images.
Details
- Language :
- English
- ISSN :
- 1662-4548
- Volume :
- 9
- Database :
- MEDLINE
- Journal :
- Frontiers in neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 26578875
- Full Text :
- https://doi.org/10.3389/fnins.2015.00418