Name
Abstract | ||
|---|---|---|
Reconstruction of white matter tracts based on diffusion tensor imaging (DTI) is currently widely used in clinical research. This reconstruction allows us to identify coordinates of specific white matter tracts and to investigate their anatomy. Fiber reconstruction, however, relies on manual identification of anatomical landmarks of a tract of interest, which is based on subjective judgment and thus a potential source of experimental variability. Here, an automated tract reconstruction approach is introduced. A set of reference regions of interest (rROIs) known to select a tract of interest was marked in our DTI brain atlas. The atlas was then linearly transformed to each subject, and the rROI set was transferred to the subject for tract reconstruction. Agreement between the automated and manual approaches was measured for 11 tracts in 10 healthy volunteers and found to be excellent (kappa>0.8) and remained high up to 4–5 mm of the linear transformation errors. As a first example, the automated approach was applied to brain tumor patients and strategies to cope with severe anatomical abnormalities are discussed. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.neuroimage.2008.04.241 | NeuroImage |
Keywords | Field | DocType |
linear transformation,artificial intelligence,algorithms,region of interest,clinical research | Computer vision,Signal processing,Diffusion MRI,White matter,Computer data storage,Psychology,Human brain,Artificial intelligence,Scanner,Soft tissue,Magnetic resonance imaging | Journal |
Volume | Issue | ISSN |
42 | 2 | 1053-8119 |
Citations | PageRank | References |
21 | 1.05 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weihong Zhang | 1 | 21 | 1.05 |
| Alessandro Olivi | 2 | 21 | 1.05 |
| Samuel J Hertig | 3 | 21 | 1.05 |
| Peter van Zijl | 4 | 1090 | 73.41 |
| Susumu Mori | 5 | 545 | 65.59 |