Fourier Transform (FT) Techniques for Markerless 4D Cone-beam CT (4D-CBCT) Sorting: Comparison between Phase vs. Magnitude

Fourier Transform (FT) Techniques for Markerless 4D Cone-beam CT (4D-CBCT) Sorting: Comparison between Phase vs. Magnitude

Proceedings of the 53rd Annual ASTRO Meeting enhancement method also removes over 80% of the streak artifacts from the FDK reconstruction results. The...

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Proceedings of the 53rd Annual ASTRO Meeting enhancement method also removes over 80% of the streak artifacts from the FDK reconstruction results. The total computation time is 610 seconds for the reconstruction algorithm and 460 seconds for the enhancement algorithm on an NVIDIA Tesla C1060 GPU card. Conclusions: By innovatively taking the temporal correlation among 4D-CBCT images into consideration, the proposed algorithms can produce high quality 4D-CBCT images with much less streak artifacts than the FDK results. Comparing the reconstruction and the enhancement algorithms, the resulted image qualities are similar. The shorter computation time makes the enhancement algorithm more attractive. Author Disclosure: X. Jia: None. Z. Tian: None. Y. Lou: None. S.B. Jiang: None.

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Fourier Transform (FT) Techniques for Markerless 4D Cone-beam CT (4D-CBCT) Sorting: Comparison between Phase vs. Magnitude

I. Vergalasova1,2, J. Cai1, F. Yin1,2 1

Duke University Medical Center, Durham, NC, 2Duke University Medical Physics Program, Durham, NC

Purpose/Objective(s): Tumors subject to respiratory-induced motion stimulate a strong motivation for 4D-imaging in order to improve the accuracy of delivered radiotherapy. Projections acquired with an on-board imager over multiple respiratory cycles (RC) can be used to form 4D-CBCT images, but correlation between respiratory phase and projection acquisition is required. This is often achieved by tracking an external marker placed on the patient’s abdomen. Studies have demonstrated that external surrogate measures may not guarantee direct correlation. Therefore, this study aims to directly extract respiratory signals from projection images based on the FT, in terms of either its phase or magnitude information. Materials/Methods: FT theory dictates that a geometrical shift in Cartesian space induces a phase shift in k-space and so organ motion occurring throughout projections should correspond to phase changes in k-space. Thus, the technique based on Fourier phase involves taking the 2D FT of each projection and plotting the phase corresponding to the same low frequency location for all projections (because the overall motion of the thorax is contained as low frequency). The technique based on magnitude also employs the FT of each projection, but instead the magnitude at the same low frequency location is plotted. These techniques rely on minimal intensity changes between projections and thus are ideal for slow-gantry acquired data. For both techniques the local minima of the resultant plots corresponded to peak inspiration. The techniques were tested with 2 sets of phantom and 3 sets of patient projections, all acquired over 200o with slow-gantry rotation speeds ranging between 0.6-0.7o/seconds. Both techniques were evaluated against the reference of visually identifying peak inspiration projections. The average differences in respiratory phase (0-100%) between Fourier and reference techniques were computed. Results: Good agreement was observed between the two techniques for the phantom studies. The average phase differences between the reference technique and the FT-phase technique for the phantom datasets were 2.25% for RC = 3s and 2.73% for RC = 6s. These values were 2.00% and 3.01%, respectively, for the FT-magnitude technique. For the three patients studied, the FT-phase resulted in average phase differences of 6.80%, 16.66%, and 16.27%, whereas the FT-magnitude resulted in values of 2.09%, 8.92%, and 1.72%, respectively. Conclusions: The average phase differences for the FT-phase technique are greater than those resulting from the FT-magnitude technique for the patient projections. This indicates that the Fourier magnitude technique is more robust than the phase technique for markerless identification of peak inspiration for 4D-CBCT reconstruction. Author Disclosure: I. Vergalasova: None. J. Cai: None. F. Yin: B. Research Grant; Varian Medical Systems.

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Scatter-free CBCT Imaging using a Beam Blocker and an Incoherence-enhancing Compressed Sensing Method

H. Lee1, B. P. Fahimian1, R. Lee2, L. Xing1 1

Stanford University, Stanford, CA, 2Ewha Woman’s University School of Medicine, Seoul, Korea, Republic of Korea

Purpose/Objective(s): X-ray scatter incurred to detector severely degrades the quality of CBCT, leading to a decrease in contrast, shading artifacts, and inaccuracies of CT number and represents a bottleneck problem in image guided and adaptive radiation therapy. The use of a beam blocker with lead strips has been proposed. Missing information obstructed by lead strips, however, requires dual scanning or dynamically moving blocker to obtain a complete image. Here we propose a novel blocker-based image acquisition and reconstruction method, allowing for simultaneous measurement of scatter and image data in a single scan, and rigorous scatter-free CBCT reconstruction in the presence of missing data. Materials/Methods: A beam blocker consisting of asymmetric lead strips parallel to axial direction of the detector is mounted to 245 mm away from the kV X-ray source of a Varian TrueBeam OBI system. In obtained projections, signals in shaded regions are attributed to the scatter data and those in unshaded regions are the image data including the primary and scatter signals. Using the scatter data on strips, 1D cubic interpolation/extrapolation is applied in the lateral direction for scatter information in unshaded regions. With scatter-corrected partial projections where the estimated scatter is subtracted from the image data, compressed sensing (CS) method is carried out by constrained optimization, which alternately uses the simultaneous algebraic reconstruction technique (SART) with interpolation and total variation (TV) regularization. The SART with interpolation is achieved by performing two separate steps. Voxels that are affected by unshaded regions in the projections are updated by SART. For updates in the rest voxels, a linear interpolation is executed using adjusted values between measured and estimated projections in subsequent unshaded regions. Consequently, the method allows for the minimization of ringing artifacts produced by differences of intensity between shaded and unshaded regions, and thus achieves incoherence from real edges when TV regularization is applied. The Catphan504 and anthropomorphic phantoms were used to evaluate the performance of the proposed method.

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