Image features for misalignment correction in medical flat‐detector CT

Wicklein, Julia; Kunze, Holger; Kalender, Willi A.; Kyriakou, Yiannis

doi:10.1118/1.4736532

Cited by 43 publications

(48 citation statements)

References 39 publications

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“…We also observed that the entropy value differences do not reflect the visual impression. In contrast to this, Kyriakou et al 37 and Wicklein et al 38 showed that entropy-based metrics are well-suited to characterizing misalignment. In our study, several contributing factors caused seemingly contradictory results.…”

Section: Discussionmentioning

confidence: 95%

“…Thus, it is possible that in the presence of severe streaks coming from multiple artifact sources, the entropy minimization procedure becomes stuck in a local minimum. Moreover, entropy-based metrics showed relatively weak performance in scans with a lower number of projection images, 38 and thus lower image quality might affect the entropy performance. To date, the entropy-based metrics have not been evaluated in the presence of multiple strong artifacts, and we have not yet investigated at which level of image noise (i.e., image quality) these metrics still function robustly.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies used entropy as a measure of misalignment-induced artifacts. 37,38 However, motion blurs out image intensities in certain pixels and thus entropy increases whereas motion-caused streaks decrease entropy. Therefore, it is not guaranteed that entropy will change monotonically as motion correction improves image quality.…”

Section: Appendix A: Histogram Entropymentioning

confidence: 99%

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Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment

et al. 2014

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Purpose: A C-arm CT system has been shown to be capable of scanning a single cadaver leg under loaded conditions by virtue of its highly flexible acquisition trajectories. In Part I of this study, using the 4D XCAT-based numerical simulation, the authors predicted that the involuntary motion in the lower body of subjects in weight-bearing positions would seriously degrade image quality and the authors suggested three motion compensation methods by which the reconstructions could be corrected to provide diagnostic image quality. Here, the authors demonstrate that a flat-panel angiography system is appropriate for scanning both legs of subjects in vivo under weight-bearing conditions and further evaluate the three motion-correction algorithms using in vivo data. Methods: The geometry of a C-arm CT system for a horizontal scan trajectory was calibrated using the PDS-2 phantom. The authors acquired images of two healthy volunteers while lying supine on a table, standing, and squatting at several knee flexion angles. In order to identify the involuntary motion of the lower body, nine 1-mm-diameter tantalum fiducial markers were attached around the knee. The static mean marker position in 3D, a reference for motion compensation, was estimated by back-projecting detected markers in multiple projections using calibrated projection matrices and identifying the intersection points in 3D of the back-projected rays. Motion was corrected using three different methods (described in detail previously): (1) 2D projection shifting, (2) 2D deformable projection warping, and (3) 3D rigid body warping. For quantitative image quality analysis, SSIM indices for the three methods were compared using the supine data as a ground truth. Results: A 2D Euclidean distance-based metric of subjects' motion ranged from 0.85 mm (±0.49 mm) to 3.82 mm (±2.91 mm) (corresponding to 2.76 to 12.41 pixels) resulting in severe motion artifacts in 3D reconstructions. Shifting in 2D, 2D warping, and 3D warping improved the SSIM in the central slice by 20.22%, 16.83%, and 25.77% in the data with the largest motion among the five datasets (SCAN5); improvement in off-center slices was 18.94%, 29.14%, and 36.08%, respectively. Conclusions: The authors showed that C-arm CT control can be implemented for nonstandard horizontal trajectories which enabled us to scan and successfully reconstruct both legs of volunteers in weight-bearing positions. As predicted using theoretical models, the proposed motion correction methods improved image quality by reducing motion artifacts in reconstructions; 3D warping performed better than the 2D methods, especially in off-center slices.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Section: Appendix A: Histogram Entropymentioning

confidence: 99%

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Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment

et al. 2014

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“…With such changes, geometric calibration is required to maximize spatial resolution in the reconstructed image data. Automated calibration methods have been developed which estimate geometric parameters based on projections of a generic object [34] and by reconstruction-based optimization of image sharpness metrics [35]. …”

Section: Technologymentioning

confidence: 99%

Micro-CT of rodents: State-of-the-art and future perspectives

2014

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Micron-scale computed tomography (micro-CT) is an essential tool for phenotyping and for elucidating diseases and their therapies. This work is focused on preclinical micro-CT imaging, reviewing relevant principles, technologies, and applications. Commonly, micro-CT provides high-resolution anatomic information, either on its own or in conjunction with lower-resolution functional imaging modalities such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). More recently, however, advanced applications of micro-CT produce functional information by translating clinical applications to model systems (e.g. measuring cardiac functional metrics) and by pioneering new ones (e.g. measuring tumor vascular permeability with nanoparticle contrast agents). The primary limitations of micro-CT imaging are the associated radiation dose and relatively poor soft tissue contrast. We review several image reconstruction strategies based on iterative, statistical, and gradient sparsity regularization, demonstrating that high image quality is achievable with low radiation dose given ever more powerful computational resources. We also review two contrast mechanisms under intense development. The first is spectral contrast for quantitative material discrimination in combination with passive or actively targeted nanoparticle contrast agents. The second is phase contrast which measures refraction in biological tissues for improved contrast and potentially reduced radiation dose relative to standard absorption imaging. These technological advancements promise to develop micro-CT into a commonplace, functional and even molecular imaging modality.

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“…In such case, nearly continuous calibration of the system's geometry should be necessary to guarantee the stability of the image spatial resolution. For this purpose, methods of self-calibration have been developed that attempt to estimate a subset of the geometric parameters of the system from the projection data of a generic object (Panetta et al, 2008) or by postreconstruction optimization of image-based metrics of image sharpness (Wicklein et al, 2012).…”

Section: Misalignment Artifactsmentioning

confidence: 99%