| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 505949 | Computers in Biology and Medicine | 2006 | 20 Pages |
Abstract
Diffusion and perfusion (MR) imaging modalities identify overlapping but not identical areas of tissue as lesion following a stroke. It is thought that the ‘mismatch’ between modalities may represent tissue that could be recovered with proper (thrombolytic) treatment. We have designed a tool for semi-automated segmentation of the images and calculation of the mismatch volume. We present results from software phantoms and clinical data. Phantom results show our mismatch volume calculations are unbiased at realistic noise levels. Clinical data show that raters using our tool are consistent, fast (15 min per subject) and indistinguishable from an expert using manual segmentation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Judy R. James, Karmen K. Yoder, Olaniyi Osuntokun, Andrew Kalnin, Askiel Bruno, Evan D. Morris,