Abstract
Purpose: X-ray scatter incurred to detectors degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, due to missing information resulting from the obstruction of the blocker, such methods require dual scanning or dynamically moving blocker to obtain a complete volumetric image. Here, we propose a half beam blocker-based approach, in conjunction with a total variation (TV) regularized Feldkamp-Davis-Kress (FDK) algorithm, to correct scatter-induced artifacts by simultaneously acquiring image and scatter information from a single-rotation CBCT scan. Methods: A half beam blocker, comprising lead strips, is used to simultaneously acquire image data on one side of the projection data and scatter data on the other half side. One-dimensional cubic B-Spline interpolation/extrapolation is applied to derive patient specific scatter information by using the scatter distributions on strips. The estimated scatter is subtracted from the projection image acquired at the opposite view. With scatter-corrected projections where this subtraction is completed, the FDK algorithm based on a cosine weighting function is performed to reconstruct CBCT volume. To suppress the noise in the reconstructed CBCT images produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by a minimization using a steepest gradient descent optimization method. The experimental studies using Catphan504 and anthropomorphic phantoms were carried out to evaluate the performance of the proposed scheme. Results: The scatter-induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the nonuniformity value was reduced from 39.3 to 3.1. The root mean square error relative to values inside the regions of interest selected from a benchmark scatter free image was reduced from 50 to 11.3. The TV regularization also led to a better contrast-to-noise ratio. Conclusions: An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.
Original language | English |
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Pages (from-to) | 2386-2395 |
Number of pages | 10 |
Journal | Medical Physics |
Volume | 39 |
Issue number | 5 |
DOIs | |
State | Published - May 2012 |
Bibliographical note
Funding Information:This work was supported by grants from the MEST (Mid-career Researcher Program, Grant No. 2009-0085999), the MKE (the Industrial Strategic Technology Development Program, Grant No. 10035495), the National Science Foundation (Grant No. 0854492), and the National Cancer Institute (Grant No. R01CA104205). We thank and acknowledge Fred van den Haak for building the blockers used in this work. TABLE I. Comparisons of CT number in seven ROIs, RMSE, and NU using the Catphan504 phantom. ROI Material of insert Benchmark image No scatter correction Subtraction only Subtraction + TV 1 Delrin™ 345.5 311.1 337.6 336.2 2 Teflon 932.9 886.3 973.1 918.9 3 Air − 971.4 − 906.4 − 1020 − 959.8 4 PMP − 174.9 − 187.9 − 208.2 − 167.5 5 LDPE − 87.3 − 71.1 − 109.3 − 80.4 6 Polystyrene − 35.1 − 2.3 − 44.1 − 31.8 7 Air − 981.1 − 889.5 − 1020.9 − 962.2 RMSE NA (not applicable) 50.0 32.3 11.3 NU 2.0 39.3 29.7 3.1 FIG. 1. Illustration of the half beam blocker setup: (a) design of the lead strips placed on the outside surface of the kV x-ray source and (b) schematic drawing to obtain the image data and the scatter data simultaneously. FIG. 2. Comparison between before and after applying an 1D cubic B-Spline interpolation and a moving-average filter: (a) the partially blocked projection data within the half region obstructed by a beam blocker and (b) the estimated scatter map to be interpolated using the scatter data inside the central one-third of each shaded region. FIG. 3. Comparison between (a) the scatter-contaminated region on the half side of a projection image and (b) the scatter-corrected region where the subtraction is completed. FIG. 4. Geometry of the scatter-corrected projection data and notations for backprojection step. FIG. 5. Comparison between the same views of the Catphan504 phantom reconstructed by applying FDK (a) without a blocker, (b) with subtraction only, and (c) with subtraction and TV regularization. These images are displayed at a window level of [ −1000,1000] HU. FIG. 6. Comparison between the same views of (a) the reconstruction image generated by the proposed scheme and (b) the benchmark image using the Catphan504 phantom. Both images are displayed at a window level of [ −1000,1000] HU and have the same voxel size of 0.55 × 0.55 × 1.25 mm. FIG. 7. Comparison of CNR calculated at seven ROIs on the reconstruction image generated by applying FDK algorithm with no scatter correction, subtraction only, and both subtraction and TV regularization: (a) seven ROIs selected on an image reconstructed by the proposed scheme and (b) CNR graph versus ROIs. FIG. 8. Comparison between the same views of the reconstruction images generated by applying (a) nonblocker based FDK algorithm, (b) nonblocker based FDK algorithm with TV regularization, (c) the proposed scheme with subtraction only, and (d) the proposed scheme with both subtraction and TV regularization using the pelvis phantom data. All images are displayed at a window level of [−1000,1000] HU. FIG. 9. Comparison between MIPs of the reconstruction images generated by applying (a) nonblocker based FDK algorithm, (b) nonblocker based FDK algorithm with TV regularization, (c) the proposed scheme with subtraction only, and (d) the proposed scheme with both subtraction and TV regularization using the pelvis phantom data. FIG. 10. Comparison between the same views of the reconstruction images generated by applying (a) nonblocker based FDK algorithm and (b) the proposed scheme with both subtraction and TV regularization using the thorax phantom data. All images are displayed at a window level of [ − 1000,1000] HU. FIG. 11. Comparison between MIPs of the reconstruction images generated by applying (a) nonblocker based FDK algorithm and (b) the proposed scheme with both subtraction and TV regularization using the thorax phantom data.
Keywords
- cone-beam CT
- FDK
- half beam blocker
- scatter correction
- total variation