Name
Title | ||
|---|---|---|
Multimodal medical image fusion using gradient domain guided filter random walk and side window filtering in framelet domain |
Abstract | ||
|---|---|---|
Since multimodal imaging technology is able to provide multiple perspectives on the lesion, it has become increasingly important in clinical diagnosis and treatment planning. In this paper, a novel medical image fusion using gradient domain-guided filter random walk (GDGFRW) and side window filtering (SWF) in the framelet transform (FT) domain is presented. Firstly, FT is performed on the original multimodal source images to obtain the corresponding approximate and residual representations. Secondly, a novel model—GDGFRW, which combines the superiorities of both gradient domain guided filtering and random walks—is constructed to interpret the approximate sub-bands, while the residual sub-bands are fused by SWF. Finally, the fused approximate sub-bands and residual sub-bands undergo inverse FT to generate the final fused image. To verify its effectiveness, the proposed method was tested on different categories of multimodal medical image fusion issues, in more than 40 pairs of source images. The proposed method outperforms the current representative ones in terms of both subjective visual performance and objective assessment. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.ins.2021.11.033 | Information Sciences |
Keywords | DocType | Volume |
Image fusion,Guided filter,Random walk,Side window filtering,Framelet transform | Journal | 585 |
ISSN | Citations | PageRank |
0020-0255 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiwei Kong | 1 | 34 | 9.67 |
| Qiguang Miao | 2 | 355 | 49.69 |
| Ruyi Liu | 3 | 0 | 0.34 |
| Yang Lei | 4 | 6 | 3.83 |
| Jing Cui | 5 | 0 | 0.34 |
| Qiang Xie | 6 | 0 | 0.34 |