Overview of X-ray Scatter in Cone-beam Computed Tomography and Its Correction Methods

Niu, Tianye; Zhu, Lin-Fan

doi:10.2174/157340510791268515

Cited by 39 publications

(42 citation statements)

References 36 publications

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“…[3][4][5] With more precise treatment monitoring from accurate CBCT images, dose delivery errors can be significantly reduced in each fraction 6,7 and further compensated for in subsequent fractions using adaptive radiation therapy. 8,9 However, the current CBCT imaging has severe shading artifacts mainly due to scatter contamination, [10][11][12][13][14] and its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a shading correction method using planning CT (pCT) as the prior knowledge.…”

Section: Introductionmentioning

confidence: 99%

Quantitative cone‐beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

2012

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Purpose: Quantitative cone-beam CT (CBCT) imaging is on increasing demand for high-performance image guided radiation therapy (IGRT). However, the current CBCT has poor image qualities mainly due to scatter contamination. Its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a correction method using planning CT (pCT) as the prior knowledge. Promising phantom results have been obtained on a tabletop CBCT system, using a correction scheme with rigid registration and without iterations. More challenges arise in clinical implementations of our method, especially because patients have large organ deformation in different scans. In this paper, we propose an improved framework to extend our method from bench to bedside by including several new components. Methods: The basic principle of our correction algorithm is to estimate the primary signals of CBCT projections via forward projection on the pCT image, and then to obtain the low-frequency errors in CBCT raw projections by subtracting the estimated primary signals and low-pass filtering. We improve the algorithm by using deformable registration to minimize the geometry difference between the pCT and the CBCT images. Since the registration performance relies on the accuracy of the CBCT image, we design an optional iterative scheme to update the CBCT image used in the registration. Large correction errors result from the mismatched objects in the pCT and the CBCT scans. Another optional step of gas pocket and couch matching is added into the framework to reduce these effects. Results: The proposed method is evaluated on four prostate patients, of which two cases are presented in detail to investigate the method performance for a large variety of patient geometry in clinical practice. The first patient has small anatomical changes from the planning to the treatment room. Our algorithm works well even without the optional iterations and the gas pocket and couch matching. The image correction on the second patient is more challenging due to the effects of gas pockets and attenuating couch. The improved framework with all new components is used to fully evaluate the correction performance. The enhanced image quality has been evaluated using mean CT number and spatial nonuniformity (SNU) error as well as contrast improvement factor. If the pCT image is considered as the ground truth, on the four patients, the overall mean CT number error is reduced from over 300 HU to below 16 HU in the selected regions of interest (ROIs), and the SNU error is suppressed from over 18% to below 2%. The average soft-tissue contrast is improved by an average factor of 2.6. Conclusions: We further improve our pCT-based CBCT correction algorithm for clinical use. Superior correction performance has been demonstrated on four patient studies. By providing quantitative CBCT images, our approach significantly increases the accuracy of advanced CBCT-based clinical applications for IGRT....

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Section: Introductionmentioning

confidence: 99%

Quantitative cone‐beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

2012

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“…With the proposed method, the RMSE of SPR estimation is reduced from 0.158 to 0.014. Since CT reconstruction accuracy is determined by SPR, not by scatter alone, 6 our method achieves sufficient scatter measurement accuracy for high-quality CT images. Figure 6 shows the reconstructed Catphan c 600 fan-beam CT images with and without considering effects of I 0 change from cone-beam to fan-beam geometry.…”

Section: Iiia Measurement Of Focal Spot Distribution and Detector Psfmentioning

confidence: 99%

“…4,5 The performance of these systems, however, is hampered by errors from large scatter contamination and beam hardening effects. 6,7 Significant research has been conducted on correction methods for these artifacts, which are able to achieve a CT number accuracy of below 50 HU in some scenarios. [8][9][10][11][12][13] As more accurate CBCT imaging is required, correction for residual CBCT artifacts becomes important.…”

Section: Introductionmentioning

confidence: 99%

Relationship between x‐ray illumination field size and flat field intensity and its impacts on x‐ray imaging

et al. 2012

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Purpose: X-ray cone-beam CT (CBCT) is being increasingly used for various clinical applications, while its performance is still hindered by image artifacts. This work investigates a new source of reconstruction error, which is often overlooked in the current CBCT imaging. The authors find that the x-ray flat field intensity (I 0 ) varies significantly as the illumination volume size changes at different collimator settings. A wrong I 0 value leads to inaccurate CT numbers of reconstructed images as well as wrong scatter measurements in the CBCT research. Methods: The authors argue that the finite size of x-ray focal spot together with the detector glare effect cause the I 0 variation at different illumination sizes. Although the focal spot of commercial x-ray tubes typically has a nominal size of less than 1 mm, the off-focal-spot radiation covers an area of several millimeters on the tungsten target. Due to the large magnification factor from the field collimator to the detector, the penumbra effects of the collimator blades result in different I 0 values for different illumination field sizes. Detector glare further increases the variation, since one pencil beam of incident x-ray is scattered into an area of several centimeters on the detector. In this paper, the authors study these two effects by measuring the focal spot distribution with a pinhole assembly and the detector point spread function (PSF) with an edge-spread function method. The authors then derive a formula to estimate the I 0 value for different illumination field sizes, using the measured focal spot distribution and the detector PSF. Phantom studies are carried out to investigate the accuracy of scatter measurements and CT images with and without considering the I 0 variation effects. Results: On our tabletop system with a Varian Paxscan 4030CB flat-panel detector and a Varian RAD-94 x-ray tube as used on a clinical CBCT system, the focal spot distribution has a measured fullwidth-at-half-maximum (FWHM) of around 0.4 mm, while non-negligible off-focal-spot radiation is observed at a distance of over 2 mm from the center. The measured detector PSF has an FWHM of 0.510 mm, with a shape close to Gaussian. From these two distributions, the author calculate the estimated I 0 values at different collimator settings. The I 0 variation mainly comes from the focal spot effect. The estimation matches well with the measurements at different collimator widths in both horizontal and vertical directions, with an average error of less than 3%. Our method improves the accuracy of conventional scatter measurements, where the scatter is measured as the difference between fan-beam and cone-beam projections. On a uniform water cylinder phantom, more accurate I 0 suppresses the unfaithful high-frequency signals at the object boundaries of the measured scatter, and the SPR estimation error is reduced from 0.158 to 0.014. The proposed I 0 estimation also reduces the reconstruction error from about 20 HU on the Catphan c 600 phantom in the selected regions of interes...

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“…Scatter correction methods for cone beam CT (CBCT) in general has been extensively investigated over the past decades, and this research topic continues to be active due to the increasing demands of CBCT in different clinical applications. Comprehensive reviews of scatter correction methods can be found in Refs …”

Section: Introductionmentioning

confidence: 99%

X-ray scatter correction for dedicated cone beam breast CT using a forward-projection model

et al. 2017

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Purpose The quality of dedicated cone-beam breast CT (CBBCT) imaging is fundamentally limited by x-ray scatter contamination due to the large irradiation volume. In this paper, we propose a scatter correction method for CBBCT using a novel forward projection model with high correction efficacy and reliability. Method We first coarsely segment the uncorrected, first-pass, reconstructed CBBCT images into binary-object maps and assign the segmented fibroglandular and adipose tissue with the correct attenuation coefficients based on the mean x-ray energy. The modified CBBCT are treated as the prior images toward scatter correction. Primary signals are first estimated via forward projection on the modified CBBCT. To avoid errors caused by inaccurate segmentation, only sparse samples of estimated primary are selected for scatter estimation. A Fourier-Transform based algorithm, herein referred to as local filtration hereafter, is developed to efficiently estimate the global scatter distribution on the detector. The scatter corrected images are obtained by removing the estimated scatter distribution from measured projection data. Results We evaluate the method performance on six patients with different breast sizes and shapes representing the general population. The results show that the proposed method effectively reduces the image spatial non-uniformity from 8.27% to 1.91% for coronal views and from 6.50% to 3.00% for sagittal views. The contrast-to-deviation ratio is improved by an average factor of 1.41. Comparisons on the image details reveal that the proposed scatter correction successfully preserves fine structures of fibroglandular tissues that are lost in the segmentation process. Conclusion We propose a highly practical and efficient scatter correction algorithm for CBBCT via a forward projection model. The method is attractive in clinical CBBCT imaging as it is readily implementable on a clinical system without modifications in current imaging protocols or system hardware.

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Overview of X-ray Scatter in Cone-beam Computed Tomography and Its Correction Methods

Cited by 39 publications

References 36 publications

Quantitative cone‐beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

Quantitative cone‐beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

Relationship between x‐ray illumination field size and flat field intensity and its impacts on x‐ray imaging

X-ray scatter correction for dedicated cone beam breast CT using a forward-projection model

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