2020
DOI: 10.1002/mp.14403
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Optimization for customized trajectories in cone beam computed tomography

Abstract: Purpose: We developed a target-based cone beam computed tomography (CBCT) imaging framework for optimizing an unconstrained three dimensional (3D) source-detector trajectory by incorporating prior image information. Our main aim is to enable a CBCT system to provide topical information about the target using a limited angle noncircular scan orbit with a minimal number of projections. Such a customized trajectory should include enough information to sufficiently reconstruct a particular volume of interest (VOI)… Show more

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Cited by 23 publications
(25 citation statements)
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“…The flexibility to rotate the patient instead of the imaging device for CBCT acquisition has already been explored in (60) and was recently taken into account for the design of the MARIE ™ proton therapy solution by Leo Cancer Care Ltd (8). If options for upright and supine positioning are foreseen, robotic CBCT systems should be able to provide the necessary flexibility, especially since they allow for non-co-planar image acquisition (61). CBCT may be a more practical solution for imaging at isocenter compared to vertical CT, not least with the recent boost in achievable CBCT image accuracy via iterative and machine learning based algorithms (7).…”
Section: Image Guidance For Upright Positionsmentioning
confidence: 99%
“…The flexibility to rotate the patient instead of the imaging device for CBCT acquisition has already been explored in (60) and was recently taken into account for the design of the MARIE ™ proton therapy solution by Leo Cancer Care Ltd (8). If options for upright and supine positioning are foreseen, robotic CBCT systems should be able to provide the necessary flexibility, especially since they allow for non-co-planar image acquisition (61). CBCT may be a more practical solution for imaging at isocenter compared to vertical CT, not least with the recent boost in achievable CBCT image accuracy via iterative and machine learning based algorithms (7).…”
Section: Image Guidance For Upright Positionsmentioning
confidence: 99%
“…However, frequency bands and scaling can be arbitrarily selected, which led to some derived metrics like the subjective quality factor [98]. Two more complicated two-dimensional metrics one encounters occasionally are the Feature Similarity Index [99] and the Visual Information Fidelity [100], which was later extended for usage with Gaussian copula functions [101] and has been used for CT-related investigations [102].…”
Section: Image Quality Metrics For Reconstruction Evaluationmentioning
confidence: 99%
“…For instance, this is particularly important for verification of advanced image reconstruction techniques. Bony tissues are considered as highly attenuation structures, which significantly affect the contrast of structures which are in proximity to bones in the reconstructed 3D image [7] . Therefore, simplified phantoms with non-realistic radiation attenuation properties for bony structures can lead to an inaccurate verification of such image reconstruction algorithms.…”
Section: Introductionmentioning
confidence: 99%