A calibration method for misaligned scanner geometry in cone-beam computed tomography

Sun, Yi; Hou, Yingkun; Feng-yong, Zhao; Hu, Jian

doi:10.1016/j.ndteint.2006.03.002

Cited by 57 publications

(44 citation statements)

References 8 publications

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“…In CBCT, the rotation of object will produce the error in all direction including x and y position. This different angle on CBCT will at least trigger the error in the vertical shift, horizontal-transversal shift from the central ray and horizontal-longitudinal shift along the central ray direction (Sun et al 2006). These three deviations can produce not only the reading of HU projection on the plane detector but also will cause the error of shape reconstruction.…”

Section: Resultsmentioning

confidence: 99%

Effect of Different Angle Scanning on Density Estimation based on Hounsfield Unit on CT and CBCT

Genisa

Rajion

Mohamad

et al. 2015

JSM

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This study aim to evaluate the effect of different angle on bone density estimation based on HU on CT and CBCT scanning. A phantom of jaw was scanned using CT and CBCT machine from different angle (0, 15 and 30 degrees). The data were transformed into DICOM format and loaded into MIMICS software for density measurement. The density was measured at 9.55 mm from cemento-enamel junction (CEJ) on every different angle scanning data. Then these data were grouped as Group A1, A2 and A3 for CBCT group (0, 15 and 30 degrees, respectively) and Group B1, B2 and B3 for CT group (0, 15 and 30 degrees, respectively (min beza = -155,63±62.61, p=0.03, min beza = -133,13±84.24, p=0,206 pada 15 dan 30 darjah imbasan). Dalam data CT, ketumpatan pada 15 dan 30 darjah imbasan adalah lebih rendah daripada 0 darjah imbasan (min beza: 84,49±46.76, p=0.09 dan 15.09±23.61, p=0,532

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Section: Resultsmentioning

confidence: 99%

Effect of Different Angle Scanning on Density Estimation based on Hounsfield Unit on CT and CBCT

Genisa

Rajion

Mohamad

et al. 2015

JSM

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“…Effects of yshifts are not clearly visible either. Many methods for the estimation of geometrical parameters of cone-beam scanners have been proposed since 1990 [20, [26][27][28][29][30]. These techniques have generally fallen into two categories: those based on iterative nonlinear optimization [26,27] and those based on the direct solution of geometric equations [20,28,29,31].…”

Section: Misalignment Correction In Single Bed Acquisitionsmentioning

confidence: 99%

“…In [27][28][29][30], either the design of this calibration object or its positioning, or both, required very high precision. Contrarily, in [20,32] the authors propose methods that avoid strict requirements on the object shape and positioning.…”

Section: Misalignment Correction In Single Bed Acquisitionsmentioning

confidence: 99%

Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners

Abella

Vaquero

Sisniega

et al. 2012

Computer Methods and Programs in Biomedicine

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Cone-beam t r a c tMost small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. (FDK). Besides the implementation of the reconstruction algorithm itself, in order to design a real system it is necessary to take into account numerous issues so as to obtain the best quality images from the acquired data. This work presents a comprehensive, novel software architecture for small-animal CT scanners based on cone-beam geometry with circular scanning trajectory. The proposed architecture covers all the steps from the system calibration to the volume reconstruction and conversion into Hounsfield units. It includes an efficient implementation of an FDK-based reconstruction algorithm that takes advantage of system symmetries and allows for parallel reconstruction using a multiprocessor computer. Strategies for calibration and artifact correction are discussed to justify the strategies adopted. New procedures for multi-bed misalignment, beam-hardening, and Housfield units calibration are proposed. Experiments with phantoms and real data showed the suitability of the proposed software architecture for an X-ray small animal CT based on cone-beam geometry. IntroductionMany small animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory [1][2][3][4]. This configuration presents advantages over other alternatives used in clinical and preclinical applications: reduction of acquisition time, large axial field of view (FOV) without geometrical distortions, and optimization of radiated dose [5]. proposed by Feldkamp et al. (FDK) [6] are still widely used for solving the 3D reconstruction task because of their straightforward implementation and computational efficiency [4]. Almost every aspect of the reconstruction process has been studied: there is literature on algorithm variations for different trajectories [7,8], optimizations using graphic processing units (GPUs) [9][10][11][12][13][14][15], strategies to reduce cone beam artifacts [16,17], study of consistency conditions [18], optimization of the back-projection step [19], etc. However, in a real practical system, the implementation of a reconstruction algorithm core such as FDK is just an initial step of the process, and there 1

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“…There are many studies about the impact of the central ray error [1][2][3][4][5] . Figure 4 shows the simulation results of introducing a 10-pixel error to the true value of the central-ray used for CT scans of a dot, a circle and a square 1 .…”

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confidence: 99%

“…Figure 4 shows the simulation results of introducing a 10-pixel error to the true value of the central-ray used for CT scans of a dot, a circle and a square 1 . The impact of the central-ray error is also demonstrated with a real IC chip.…”

mentioning

confidence: 99%

Differential Cone-Beam CT Reconstruction for Planar Objects

Liu¹

2011

Computed Tomography - Special Applications

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A calibration method for misaligned scanner geometry in cone-beam computed tomography

Cited by 57 publications

References 8 publications

Effect of Different Angle Scanning on Density Estimation based on Hounsfield Unit on CT and CBCT

Effect of Different Angle Scanning on Density Estimation based on Hounsfield Unit on CT and CBCT

Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners

Differential Cone-Beam CT Reconstruction for Planar Objects

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