Name
Abstract | ||
|---|---|---|
Accurate rodent brain extraction is one of the basic steps for many translational study using Magnetic Resonance Imaging (MRI). In this paper, we present a new approach to model the rodent brain variation using non-rigid B-spline image registration for the brain extraction in MRI images. We model the shape and appearance with the B-spline parameters together with a mean brain image. Followed by a method using multi-expert, we refine the brain extraction region. Compared with the image-based template model using cross-correlation, the performance for rodent brain extraction has shown much improvement on one data set while maintaining the similar yet more consistent performance for another. Both template based methods however outperform the voxel based method (3D PCNN) and a modified BET version for rodent brain extraction. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/EMBC.2017.8036825 | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
Keywords | Field | DocType |
Algorithms,Animals,Brain,Magnetic Resonance Imaging,Rodentia | Voxel,B-spline,Computer vision,Computer science,Artificial intelligence,Image registration,Magnetic resonance imaging | Conference |
Volume | ISSN | ISBN |
2017 | 1557-170X | 978-1-5090-2810-8 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weimin Huang | 1 | 1074 | 96.95 |
| Chen Ling | 2 | 0 | 2.03 |
| Huang Su | 3 | 10 | 2.29 |
| Zhongkang Lu | 4 | 577 | 46.90 |
| Zhiping Lin | 5 | 291 | 37.46 |