Non-Parametric Image Subtraction for MRI |
Abstract |
Image subtraction is used in many areas of machine vision to identify small changes between equivalent pairs of images. Often only a small subset of the differences will be of interest. For example, MS lesions can be detected by subtraction of MRI scans taken before and after the injection of GdDTPA contrast agent. The contrast agent highlights the lesions, but also results in global changes in the post-injection scan. Simple image subtraction detects all differences regardless of their source, and is therefore problematic to use. Superior techniques, analogous to standard statistical tests, can isolate localised differences due to lesions from global differences. We introduce a new non-parametric statistical measure which allows a direct probabilistic interpretation of image differences. We expect this to be applicable to a wide range of image formation processes. Its application to medical images is discussed.
Download |
pab_miua2001_paper.pdf (180kB)
In addition, you can view the poster (313kB) I presented, or the handout (216kB) I prepared on the statistical theory underlying the non-parametric image subtraction technique.