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Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the photoacoustically induced initial pressure distribution within tissue. The PACT reconstruction problem corresponds to a time-domain inverse source problem, where the initial pressure distribution is recovered from the measurements recorded on an aperture outside the support of the source. A major challenge in transcranial PACT of the brain...
Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study.
Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusion (CTP).
Iterative reconstruction has become the standard method for reconstructing computed tomography (CT) scans and needs to be verified for adaptation.
This study aimed to evaluate image quality of ultra-low dose chest computed tomography using 6 iterative reconstruction (IR) algorithms.
This study aimed to evaluate potential dose savings on a revised protocol for whole-body computed tomography and image quality after implementing Adaptive Statistical Iterative Reconstruction V (ASiR-V) algorism for trauma patients and compare it with routine protocol.
Model-based iterative reconstruction is a promising approach to achieve dose reduction without affecting image quality in diagnostic x-ray computed tomography (CT). In the problem formulation, it is common to enforce non-negative values to accommodate the physical non-negativity of x-ray attenuation. Using this a priori information is believed to be beneficial in terms of image quality and convergence speed. However, enforcing non-negativity imposes limitations on the problem formulation and the choice of o...
In emission tomography, iterative image reconstruction from noisy measured data usually results in noisy images, and so regularisation is often used to compensate for noise. However, in practice, an appropriate, automatic and precise specification of the strength of regularisation for image reconstruction from a given noisy measured dataset remains unresolved. Existing approaches are either empirical approximations with no guarantee of generalisation, or else are computationally intensive cross-validation m...
Image-based noise reduction techniques are useful because they can be applied across various computed tomography (CT) scanner models from different vendors, regardless of the iterative reconstruction availability. The purpose of this study was to propose a 3-dimensional cross-directional bilateral filter (3D-CDBF) and compare the edge-preserving noise reduction on low-dose CT images to a model-based iterative reconstruction (MBIR).
Retrospective OBJECTIVE.: To evaluate the image quality of low-radiation-dose computed tomography (LD-CT) of the thoracolumbar spine, using model-based iterative reconstruction (MBIR) for measuring pedicle diameter.
The purpose of this study was to investigate the visualization of fine biliary ducts with knowledge-based iterative model reconstruction (IMR) in low-dose drip infusion CT cholangiography (DIC-CT) as compared with filtered back projection (FBP) and hybrid iterative reconstruction (iDose ).
To evaluate the effect of ultra high-resolution computed tomography (UHRCT) and model-based iterative reconstruction (MBIR) on the detectability of simulated submillimeter artery.
Positron emission tomography (PET) image reconstruction is usually performed using maximum likelihood (ML) iterative reconstruction methods, under the assumption of Poisson distributed data. Pre-correcting raw measured counts, this assumption is no longer realistic. The goal of this work is to develop a reconstruction algorithm based on the Negative Binomial (NB) distribution, which can generalize over the Poisson distribution in case of over-dispersion of raw data, that may occur if sinogram pre-correction...
Image quality of early postoperative CT angiography with reduced contrast material and radiation dose using model-based iterative reconstruction for screening of renal pseudoaneurysms after partial nephrectomy.
To evaluate the image quality of early postoperative CT angiography with low contrast material and radiation dose using model-based iterative reconstruction (FIRST) for screening pseudoaneurysms after partial nephrectomy.
Photoacoustic tomography is an imaging modality based on the photoacoustic effect caused by the absorption of an externally introduced light pulse. In the inverse problem of photoacoustic tomography, the initial pressure generated through the photoacoustic effect is estimated from a measured photoacoustic time-series utilizing a forward model for ultrasound propagation. Due to the ill-posedness of the inverse problem, errors in the forward model or measurements can result in significant errors in the soluti...
Numerous image reconstruction methodologies for positron emission tomography (PET) have been developed that incorporate magnetic resonance (MR) imaging structural information, producing reconstructed images with improved suppression of noise and reduced partial volume effects. However, the influence of MR structural information also increases the possibility of suppression or bias of structures present only in the PET data (PET-unique regions). To address this, further developments for MR-informed methods h...
Photoacoustic tomography (PAT) is an emerging and effective imaging technique, which owns high spatial resolution with high contrast. In particular, the acquired data is incomplete due to geometrical limitations or accelerating data acquisition by undersampling technology, thus some artifacts will be presented in the reconstructed image. To deal with limited-view PAT, we introduce a l0 regularization scheme into PAT and propose a three-stage method. We first use the gradient descent method to obtain an init...
To evaluate radiation dose exposure, diagnostic performance, and image quality of low-dose and ultralow-dose abdominopelvic CT using the advanced modelled iterative reconstruction (ADMIRE) algorithm for focal lesion detection.
As x-ray microscopy is pushed into the nanoscale with the advent of more bright and coherent x-ray sources, associated improvement in spatial resolution becomes highly vulnerable to geometrical errors and uncertainties during data collection. We address a form of error in tomography experiments, namely, the drift between projections during the tomographic scan. Our proposed method can simultaneously recover the drift, while tomographically reconstructing the specimen based on a joint iterative optimization ...
To reduce the magnetic resonance imaging (MRI) data acquisition time and improve the MR image reconstruction performance, reconstruction algorithms based on the iterative shrinkage thresholding algorithm (ISTA) are widely used. However, these traditional algorithms use global threshold shrinkage, which is not efficient. In this paper, a novel algorithm based on local threshold shrinkage, which is called the local shrinkage thresholding algorithm (LSTA), was proposed. The LSTA can shrink differently for diff...
To compare the effects of hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) that incorporates a beam-hardening model for myocardial extracellular volume (ECV) quantification by cardiac CT using MRI as a reference standard.
To reduce the cost of positron emission tomography (PET) scanning systems, image reconstruction algorithms for low-sampled data have been extensively studied. However, the current method based on total variation (TV) minimization regularization nested in the maximum likelihood-expectation maximization (MLEM) algorithm cannot distinguish true structures from noise resulting losing some fine features in the images. Thus, this work aims to recover fine features lost in the MLEM-TV algorithm from low-sampled da...
Magnetic induction tomography (MIT) is a non-invasive modality for imaging the complex conductivity (σ) or the magnetic permeability (μ) of a target under investigation. The critical issue in the clinical application of the detection of cerebral hemorrhage is the determination of intracranial hematoma status, including the location and volume of intracranial hematoma. In MIT, the reconstruction image is used to reflect intracranial hematoma. However, in medical applications where high resolutions are soug...
The circular-edge technique using a low-contrast cylindrical object is commonly used to measure the modulation transfer functions (MTFs) in computed tomography (CT) images reconstructed with iterative reconstruction (IR) algorithms. This method generally entails averaging multiple images of the cylinder to reduce the image noise. We suspected that the cylinder edge shape depicted in the IR images might exhibit slight deformation with respect to the true shape because of the intrinsic nonlinearity of IR algo...
As a low-end computed tomography (CT) system, translational CT (TCT) is in urgent demand in developing countries. Under some circumstances, in order to reduce the scan time, decrease the X-ray radiation or scan long objects, furthermore, to avoid the inconsistency of the detector for the large angle scanning, we use the limited-angle TCT scanning mode to scan an object within a limited angular range. However, this scanning mode introduces some additional noise and limited-angle artifacts that seriously degr...
Computed Tomography Angiography Combined With Knowledge-Based Iterative Algorithm for Transcatheter Aortic Valve Implantation Planning: Image Quality and Radiation Dose Exposure With Low-kV and Low-Contrast-Medium Protocol.
To evaluate image quality and radiation dose exposure of low-kV setting and low-volume contrast medium (CM) computed tomography angiography (CTA) protocol for transcatheter aortic valve implantation (TAVI) planning in comparison with standard CTA protocol.