Name
Abstract | ||
|---|---|---|
High-density objects, such as metal prostheses or surgical clips, generate streak-like artifacts in CT images. We designed a, radial adaptive filter, which directly operates on the corrupted reconstructed image, to effectively and efficiently reduce such artifacts. The filter adapts to the severity of local artifacts to preserve spatial resolution as much as possible. The widths and direction of the filter are derived from the local structure tensor. Visual inspection shows that this novel radial adaptive filter is superior with respect to existing methods in the case of mildly distorted images. In the presence of strong artifacts we propose a, hybrid approach. An image, corrected with a, standard method, which performs well oil images with regions of severe artifacts, is fused with an adaptively filtered clone to combine the strengths of both methods. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1117/12.593095 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
computed tomography,metal artifacts,adaptive filtering,structure tensor | Metal Artifact,Computer vision,Visual inspection,Tensor,Local structure,Surgical Clips,Artificial intelligence,Adaptive filter,Engineering,Image resolution | Conference |
Volume | ISSN | Citations |
5747 | 0277-786X | 1 |
PageRank | References | Authors |
0.37 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| matthieu bal | 1 | 1 | 0.37 |
| hasan celik | 2 | 1 | 0.37 |
| krishna subramanyan | 3 | 14 | 4.60 |
| Eck Kai | 4 | 52 | 7.57 |
| lothar spies | 5 | 3 | 1.07 |