Name
Abstract | ||
|---|---|---|
In the present work, a recent proposed transformation domain filter algorithm (BM3D) using the sparseness and self-similarity properties of the images is presented and adapted to reduce the specific Rician distribution noise in MRI magnitude images. The proposed R-BM3D method is compared to the state-of-the-art transformation domain filter method (ODCT3D), which is proved to be superior to the blockwise nonlocal means filter, the wavelet sub-band coefficient mixing method, and the anisotropic diffusion filter. Comparative experimental results indicate that the proposed R-BM3D is quite competitive in RMSE metric, filter time and visual inspection. © 2011 IEEE. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/BMEI.2011.6098330 | BMEI |
Keywords | Field | DocType |
denoise,mri,sparsness,transformation domain,collaborative filtering,noise measurement,noise reduction,three dimensional,anisotropic diffusion,magnetic resonance image,visual inspection | Computer vision,Magnitude (mathematics),Visual inspection,Collaborative filtering,Pattern recognition,Computer science,Mean squared error,Kernel adaptive filter,Artificial intelligence,Filter algorithm,Rician fading,Wavelet | Conference |
Volume | Issue | Citations |
1 | null | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangbo Lin | 1 | 7 | 1.49 |
| Tianshuang Qiu | 2 | 313 | 43.84 |