Data Consistency Based Rigid Motion Artifact Reduction in Fan-Beam CT

Yu, Hengyong; Wang, Ge

doi:10.1109/tmi.2006.889717

Cited by 75 publications

(43 citation statements)

References 24 publications

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“…For fan beam or cone beam OPT motion estimation, we suggest the work on fan beam X-ray CT motion calibration [37], [38]. It should be noted that there are some limitations to our approach: firstly, projection truncation is not allowable, a restriction which results from the consistency condition.…”

Section: Discussionmentioning

confidence: 99%

“…In order to quantitatively evaluate the motion estimation results, the mean translation excursion (MTE) and the mean rotation excursion (MRE) are defined as follows [38]: (22) (23) where , and . is the total scanning time, and is set to 1 s in all the simulation experiments.…”

Section: Quantitative Evaluationmentioning

confidence: 99%

“…is the total scanning time, and is set to 1 s in all the simulation experiments. Let and denote the estimated values of the translation and rotation functions, respectively, then the relative mean translation excursion (rMTE) and the relative mean rotation excursion (rMRE) are defined as [38] (24) (25) It is clear that the above metrics are just suitable to evaluate the motion estimation results of simulation experiments in which the object motion is known beforehand. In a real experimental situation the object motion is unknown, thus other evaluating indicators should be introduced.…”

Section: Quantitative Evaluationmentioning

confidence: 99%

“…It has been utilized to reduce X-ray CT image artifacts and to estimate unknown view angles [35], [36]. Based on this consistency condition, Yu et al proposed motion estimation methods for fan-beam X-ray CT scanner [37], [38]. Using an equivalent approach, we make use of the consistency condition to account for specimen motion in parallel beam OPT.…”

mentioning

confidence: 99%

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Automated Motion Correction for In Vivo Optical Projection Tomography

Zhu

Dong²,

Birk

et al. 2012

IEEE Trans. Med. Imaging

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Abstract-In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion.

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Section: Discussionmentioning

confidence: 99%

Section: Quantitative Evaluationmentioning

confidence: 99%

Section: Quantitative Evaluationmentioning

confidence: 99%

mentioning

confidence: 99%

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Automated Motion Correction for In Vivo Optical Projection Tomography

Zhu

Dong²,

Birk

et al. 2012

IEEE Trans. Med. Imaging

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“…[20][21][22] Yu and Wang extended another method that reduces motion artefacts based on data consistency. 23 The existing methods described in the literature for motion detection and correction are limited to specifi c motions and conditions. They usually cannot improve the image quality as well as a motion-free one.…”

Section: Introductionmentioning

confidence: 99%

Real-time axial motion detection and correction for single photon emission computed tomography using a linear prediction filter

2011

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Effect of subject motion and gantry rotation speed on image quality and dose delivery in CT‐guided radiotherapy

et al. 2022

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To investigate the effects of subject motion and gantry rotation speed on computed tomography (CT) image quality over a range of image acquisition speeds for fan-beam (FB) and cone-beam (CB) CT scanners, and quantify the geometric and dosimetric errors introduced by FB and CB sampling in the context of adaptive radiotherapy. Methods: Images of motion phantoms were acquired using four CT scanners with gantry rotation speeds of 0.5 s/rotation (denoted FB-0.5), 1.9 s/rotation (FB-1.9), 16.6 s/rotation (CB-16.6), and 60.0 s/rotation (CB-60.0). A phantom presenting various tissue densities undergoing motion with 4-s period and ranging in amplitude from ±0.5 to ±10.0 mm was used to characterize motion artifacts (streaks), motion blur (edge-spread function, ESF), and geometric inaccuracy (excursion of insert centroids and distortion of known shape). An anthropomorphic abdomen phantom undergoing ±2.5-mm motion with 4-s period was used to simulate an adaptive radiotherapy workflow, and relative geometric and dosimetric errors were compared between scanners. Results: At ±2.5-mm motion, phantom measurements demonstrated mean ± SD ESF widths of 0.6 ± 0.0, 1.3 ± 0.4, 2.0 ± 1.1, and 2.9 ± 2.0 mm and geometric inaccuracy (excursion) of 2.7 ± 0.4, 4.1 ± 1.2, 2.6 ± 0.7, and 2.0 ± 0.5 mm for the FB-0.5, FB-1.9, CB-16.6, and CB-60.0 scanners, respectively. The results demonstrated nonmonotonic trends with scanner speed for FB and CB geometries. Geometric and dosimetric errors in adaptive radiotherapy plans were largest for the slowest (CB-60.0) scanner and similar for the three faster systems (CB-16.6, FB-1.9, and FB-0.5). Conclusions: Clinically standard CB-60.0 demonstrates strong image quality degradation in the presence of subject motion, which is mitigated through faster CBCT or FBCT. Although motion blur is minimized for FB-0.5 and FB-1.9, such systems suffer from increased geometric distortion compared to CB-16.6. Each system reflects tradeoffs in image artifacts and geometric inaccuracies that affect treatment delivery/dosimetric error and should be considered in the design of next-generation CT-guided radiotherapy systems.

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Data Consistency Based Rigid Motion Artifact Reduction in Fan-Beam CT

Cited by 75 publications

References 24 publications

Automated Motion Correction for In Vivo Optical Projection Tomography

Automated Motion Correction for In Vivo Optical Projection Tomography

Real-time axial motion detection and correction for single photon emission computed tomography using a linear prediction filter

Effect of subject motion and gantry rotation speed on image quality and dose delivery in CT‐guided radiotherapy

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