Kinect-Based Correction of Overexposure Artifacts in Knee Imaging with C-Arm CT Systems

Rausch, Johannes; Maier, Andreas; Fahrig, Rebecca; Choi, Jang-Hwan; Hinshaw, W. S.; Schebesch, Frank; Haase, Sven; Wasza, Jakob; Hornegger, Joachim; Rieß, Christian

doi:10.1155/2016/2502486

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…Despite the encouraging results achieved in this study, the proposed method still has several limitations: (1) real data experiments have to be conducted in order to demonstrate its practical applicability. To this end, technical challenges such as cross calibration or synchronization of both systems have to be overcome [46,47]; (2) only three dimensional rigid motion was simulated and estimated that does not reflect realistic patient motion. Motion of human joints is a highly complex combination of multiple rigid body transformations of the bony and deformable displacements of the surrounding soft tissue.…”

Section: Discussionmentioning

confidence: 99%

Range Imaging for Motion Compensation in C-Arm Cone-Beam CT of Knees under Weight-Bearing Conditions

et al. 2018

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C-arm cone-beam computed tomography (CBCT) has been used recently to acquire images of the human knee joint under weight-bearing conditions to assess knee joint health under load. However, involuntary patient motion during image acquisition leads to severe motion artifacts in the subsequent reconstructions. The state-of-the-art uses fiducial markers placed on the patient's knee to compensate for the induced motion artifacts. The placement of markers is time consuming, tedious, and requires user experience, to guarantee reliable motion estimates. To overcome these drawbacks, we recently investigated whether range imaging would allow to track, estimate, and compensate for patient motion using a range camera. We argue that the dense surface information observed by the camera could reveal more information than only a few surface points of the marker-based method. However, the integration of range-imaging with CBCT involves flexibility, such as where to position the camera and what algorithm to align the data with. In this work, three dimensional rigid body motion is estimated for synthetic data acquired with two different range camera trajectories: a static position on the ground and a dynamic position on the C-arm. Motion estimation is evaluated using two different types of point cloud registration algorithms: a pair wise Iterative Closest Point algorithm as well as a probabilistic group wise method. We compare the reconstruction results and the estimated motion signals with the ground truth and the current reference standard, a marker-based approach. To this end, we qualitatively and quantitatively assess image quality. The latter is evaluated using the Structural Similarity (SSIM). We achieved results comparable to the marker-based approach, which highlights the potential of both point set registration methods, for accurately recovering patient motion. The SSIM improved from 0.94 to 0.99 and 0.97 using the static and the dynamic camera trajectory, respectively. Accurate recovery of patient motion resulted in remarkable reduction in motion artifacts in the CBCT reconstructions, which is promising for future work with real data.

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Section: Discussionmentioning

confidence: 99%

Range Imaging for Motion Compensation in C-Arm Cone-Beam CT of Knees under Weight-Bearing Conditions

et al. 2018

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“…It assumes that there is no noise in the saturated measurements. Thus model (11) is not suitable when there is noise in measurements before quantization. In fact, model ( 11) is equivalent to model ( 5) with τ = 0, λ = +∞, and c = +∞.…”

Section: Experimental Validationmentioning

confidence: 99%

“…However, the method is not ideal since the modeling clay may cause great discomfort for the patient. Alternatively, a Kinect camera was used to obtain the object depth information, which can be combined into a C-arm system for correcting overexposured projections [11]. More specifically, the Kinect depth data is used to find the points of intersection between the X-ray beam path and object surface.…”

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confidence: 99%

Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction

Huang,

Xia,

Shi

et al. 2017

Preprint

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When a measurement falls outside the quantization or measurable range, it becomes saturated and cannot be used in classical reconstruction methods. For example, in Carm angiography systems, which provide projection radiography, fluoroscopy, digital subtraction angiography, and are widely used for medical diagnoses and interventions, the limited dynamic range of C-arm flat detectors leads to overexposure in some projections during an acquisition, such as imaging relatively thin body parts (e.g., the knee). Aiming at overexposure correction for computed tomography (CT) reconstruction, we in this paper propose a mixed one-bit compressive sensing (M1bit-CS) to acquire information from both regular and saturated measurements. This method is inspired by the recent progress on one-bit compressive sensing, which deals with only sign observations. Its successful applications imply that information carried by saturated measurements is useful to improve recovery quality. For the proposed M1bit-CS model, alternating direction methods of multipliers is developed and an iterative saturation detection scheme is established. Then we evaluate M1bit-CS on one-dimensional signal recovery tasks. In some experiments, the performance of the proposed algorithms on mixed measurements is almost the same as recovery on unsaturated ones with the same amount of measurements. Finally, we apply the proposed method to overexposure correction for CT reconstruction on a phantom and a simulated clinical image. The results are promising, as the typical streaking artifacts and capping artifacts introduced by saturated projection data are effectively reduced, yielding significant error reduction compared with existing algorithms based on extrapolation.

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“…Huang et al [13], [14] propose a recovery method called mixed one-bit compressive sensing, which yields promising results on numerical simulations but needs prior knowledge of the location of saturated pixels. Rausch et al [15] used a depth camera to reconstruct the skin border requiring external hardware and manual input.…”

Section: Introductionmentioning

confidence: 99%

3D Non-Rigid Alignment of Low-Dose Scans Allows to Correct for Saturation in Lower Extremity Cone-Beam CT

Maier

Eskofier

et al. 2021

IEEE Access

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Detector saturation in cone-beam computed tomography occurs when an object of highly varying shape and material composition is imaged using an automatic exposure control (AEC) system. When imaging a subject's knees, high beam energy ensures the visibility of internal structures but leads to overexposure in less dense border regions. In this work, we propose to use an additional low-dose scan to correct the saturation artifacts of AEC scans. Overexposed pixels are identified in the projection images of the AEC scan using histogram-based thresholding. The saturation-free pixels from the AEC scan are combined with the skin border pixels of the low-dose scan prior to volumetric reconstruction. To compensate for patient motion between the two scans, a 3D non-rigid alignment of the projection images in a backward-forward-projection process based on fiducial marker positions is proposed. On numerical simulations, the projection combination improved the structural similarity index measure from 0.883 to 0.999. Further evaluations were performed on two in vivo subject knee acquisitions, one without and one with motion between the AEC and low-dose scans. Saturation-free reference images were acquired using a beam attenuator. The proposed method could qualitatively restore the information of peripheral tissue structures. Applying the 3D non-rigid alignment made it possible to use the projection images with inter-scan subject motion for projection image combination. The increase in radiation exposure due to the additional low-dose scan was found to be negligibly low. The presented methods allow simple but effective correction of saturation artifacts.

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Kinect-Based Correction of Overexposure Artifacts in Knee Imaging with C-Arm CT Systems

Cited by 5 publications

References 25 publications

Range Imaging for Motion Compensation in C-Arm Cone-Beam CT of Knees under Weight-Bearing Conditions

Range Imaging for Motion Compensation in C-Arm Cone-Beam CT of Knees under Weight-Bearing Conditions

Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction

3D Non-Rigid Alignment of Low-Dose Scans Allows to Correct for Saturation in Lower Extremity Cone-Beam CT

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