Name
Abstract | ||
|---|---|---|
One aim of this work is to investigate the feasibility of using a hierarchy of models to describe diffusion tensor MRI data. Parsimonious model selection criteria are used to choose among different models of diffusion within tissue. Second, based on this information, we assess whether we can perform simultaneous tissue segmentation and classification. The proposed hierarchical framework used for parsimonious model selection is based on the F-test, adapted from Snedecor. Diffusion Magnetic Resonance Microscopy (MRM) provides near-microscopic resolution without relying on a sample's optical transparency for image formation. Diffusion MRM is a noninvasive imagring technique for quantitative analysis of intrinsic features of tissues. Thus, we propose using Diffusion MRM to characterize normal tissue structure in adult zebrafish, and possibly subtle anatomical or structural differences between normals and knockouts. Both numerical phantoms and diffusion weighted image (DWI) data obtained from adult zebrafish are used to test this model selection framework. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1117/12.708312 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
DTI,diffusion tensor,MRI,hierarchical,parsimonious,model selection | Optical transparency,Computer vision,Diffusion MRI,Pattern recognition,Magnetic resonance microscopy,Segmentation,Zebrafish,Model selection,Chemistry,Image formation,Artificial intelligence,Noninvasive imaging | Conference |
Volume | ISSN | Citations |
6512 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raisa Z. Freidlina | 1 | 0 | 0.34 |
| Michal E Komlosh | 2 | 44 | 4.33 |
| Murray H. Loew | 3 | 151 | 47.53 |
| Peter J Basser | 4 | 459 | 57.03 |