Name
Abstract | ||
|---|---|---|
In this paper, we propose a method to accurately register CT to cone-beam CT (CBCT) by iteratively correcting local CBCT intensity. CBCT is a widely used intra-operative imaging modality in image-guided radiotherapy and surgery. A short scan followed by a filtered-backprojection is typically used for CBCT reconstruction. While data on the mid-plane (plane of source-detector rotation) is complete, off-mid-planes undergo different information deficiency and the computed reconstructions are approximate. This causes different reconstruction artifacts at off-mid-planes depending on slice locations, and therefore impedes accurate registration between CT and CBCT. To address this issue, we correct CBCT intensities by matching local intensity histograms slice by slice in conjunction with intensity-based deformable registration. This correction-registration step is repeated until the result image converges. We tested the proposed method on eight head-and-neck cancer cases and compared its performance with state-of-the-art registration methods, B-spline, demons, and optical flow, which are widely used for CT-CBCT registration. Normalized mutual-information (NMI), normalized cross-correlation (NCC), and structural similarity (SSIM) were computed as similarity measures for the performance evaluation. Our method produced overall NMI of 0.59, NCC of 0.96, and SSIM of 0.93, outperforming existing methods by 3.6%, 2.4%, and 2.8% in terms of NMI, NCC, and SSIM scores, respectively. Experimental results show that our method is more consistent and roust than existing algorithms, and also computationally efficient with faster convergence. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1117/12.2082485 | Proceedings of SPIE |
Keywords | Field | DocType |
CBCT,deformable registration,intensity correction | Computer vision,Histogram,Normalization (statistics),Artificial intelligence,Beam (structure),Optical flow,Physics | Conference |
Volume | ISSN | Citations |
9413 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seyoun Park | 1 | 53 | 4.88 |
| William Plishker | 2 | 138 | 16.11 |
| Raj Shekhar | 3 | 282 | 32.08 |
| Harry Quon | 4 | 4 | 1.44 |
| John Wong | 5 | 6 | 3.26 |
| Junghoon Lee | 6 | 38 | 7.21 |