Name
Abstract | ||
|---|---|---|
We present a set of new methods for efficient and precise registration of any X-Ray modality (fluoroscopy, portal imaging or regular X-Ray imaging) to a CT data set. These methods require neither feature extraction nor 2D or 3D segmentation. Our main contribution is to directly perform the computations on the gradient vector volume of the CT data, which has several advantages. It can increase the precision of the registration as it assesses mainly the alignment of intensity edges in both CT and X-Ray images. By using only significant areas of the gradient vector volume, the amount of information needed in each registration step can be reduced up to a factor of 10. This both speeds up the registration process and allows for using the CT data with full precision, e.g. 512(3) voxels. We introduce a Volume Gradient Rendering (VGR) as well as a Volume Gradient Correlation (VGC) method, where the latter one can be used directly for computing the image similarity without DRR generation. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1117/12.595466 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
feature extraction | Voxel,Computer vision,Segmentation,Fluoroscopy,Feature extraction,Artificial intelligence,Rendering (computer graphics),Image registration,Mathematics,Computation | Conference |
Volume | ISSN | Citations |
5747 | 0277-786X | 6 |
PageRank | References | Authors |
0.59 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wolfgang Wein | 1 | 461 | 38.75 |
| Barbara Roper | 2 | 46 | 4.92 |
| Nassir Navab | 3 | 6594 | 578.60 |