Reduction of blooming artifacts in cardiac CT images by blind deconvolution and anisotropic diffusion filtering

Castillo-Amor, Angélica M.; Navarro-Navia, Cristian A.; Cadena, Alberto; Contreras-Ortiz, Sonia H.

doi:10.1117/12.2209217

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Previously, others have adopted this deconvolution approach to reduce calcium blooming from vascular calcifications, 3,5 iterative deblurring for CT metal artifact reduction, 6 and improving stent delineation in cardiac CT images. 7 The purpose of this study was to enable accurate assessment of the CT numbers in an arterial wall by reducing blooming effects from contrast media in the lumen using image deconvolution and to demonstrate the feasibility of detecting increased VV (IVV) density in the carotid artery using a large animal model and a whole-body photon-counting CT (PCCT) system.…”

Section: Introductionmentioning

confidence: 99%

Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution

et al. 2017

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Changes in arterial wall perfusion mark the onset of atherosclerosis. A characteristic change is the increased spatial density of vasa vasorum (VV), the microvessels in the arterial walls. Measuring this increased VV (IVV) density using contrast-enhanced computed tomography (CT) has had limited success due to blooming effects from contrast media. If the system point-spread function (PSF) is known, then the blooming effect can be modeled as a convolution between the true signal and the PSF. We report the application of image deconvolution to improve the CT number accuracy in the arterial wall of a phantom and in a porcine model of IVV density, both scanned using a whole-body research photon-counting CT scanner. A 3D-printed carotid phantom filled with three concentrations of iodinated contrast material was scanned to assess blooming and its effect on wall CT number accuracy. The results showed a reduction in blooming effects following image deconvolution, and, consequently, a better delineation between lumen and wall was achieved. Results from the animal experiment showed improved CT number difference between the carotid with IVV density and the normal carotid artery after deconvolution, enabling the detection of VV proliferation, which may serve as an early indicator of atherosclerosis.

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Section: Introductionmentioning

confidence: 99%

Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution

et al. 2017

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A Three-Dimensional Quantification of Calcified and Non-calcified Plaque Based on Computed Tomography Coronary Angiography Images: Comparison with Virtual Histology Intravascular Ultrasound

et al. 2018

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The identification, quantification and characterization of coronary atherosclerotic plaque has a major influence on diagnosis and treatment of coronary artery disease (CAD). Recent studies have reported the ability of Computed Tomography Coronary Angiography (CTCA) to identify non-invasively coronary plaque features. In this study, we present a novel methodology for the identification of the plaque burden of the coronary artery and the volumetric quantification of calcified plaques (CP) and non-calcified plaques (NCP), utilizing CTCA images in comparison with virtual histology intravascular ultrasound (VH-IVUS). The proposed methodology includes six steps: CTCA images pre-processing, vessel centerline extraction using Multistencil Fast Marching Method (MSFM), estimation of membership sigmoidal distribution functions, implementation of an extension of active contour models using prior shapes for the lumen, the outer wall and CP segmentation, detection and quantification of NCP and finally three-dimensional (3D) models construction. Bland-Altman analyses were performed to assess the agreement between the presented methodology and VH-IVUS. Assessment of CP and NCP volume and length of lesion length 18 lesions indicated excellent correlation with VH-IVUS, (r = 0.92, p < 0.001), (r= 0.95, p < 0.001) and (r= 0.81, p < 0.001), respectively.

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Reduction of blooming artifacts in cardiac CT images by blind deconvolution and anisotropic diffusion filtering

Cited by 2 publications

References 12 publications

Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution

Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution

A Three-Dimensional Quantification of Calcified and Non-calcified Plaque Based on Computed Tomography Coronary Angiography Images: Comparison with Virtual Histology Intravascular Ultrasound

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