Name
Abstract | ||
|---|---|---|
The importance of small animal imaging in fundamental and clinical research is growing rapidly. These studies typically involve micro PET, micro MR, and micro CT images as well as optical or fluorescence images. Hstological images are also often used to complement and/or validate the in vivo data. As is the case for human studies, automatic registration of these imaging modalities is a critical component of the overall analysis process, but, the small size of the animals and thus the limited spatial resolution of the in vivo images present specific challenges. In this paper, we propose a series of methods and techniques that permit the inter-subject registration of micro MR and histological images. We then compare results obtained by registering directly MR volumes to each other using a non-rigid registration algorithm we have developed at our institution with results obtained by registering first the MR volumes to their corresponding histological volume, which we reconstruct from 2D cross-sections, and then registering histological volumes to each other. We show that the second approach is preferable. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1117/12.652407 | Proceedings of SPIE |
Keywords | Field | DocType |
image segmentation,registration,reconstruction,atlas | Computer vision,Imaging modalities,Computer science,Image segmentation,Artificial intelligence,Animal imaging,Image resolution,Modal | Conference |
Volume | ISSN | Citations |
6144 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xia Li | 1 | 16 | 3.19 |
| Thomas E. Yankeelov | 2 | 20 | 7.14 |
| Glenn D Rosen | 3 | 41 | 9.50 |
| John C Gore | 4 | 616 | 41.36 |
| Benoit M. Dawant | 5 | 1388 | 223.11 |