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iterative model reconstruction

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https://www.readbyqxmd.com/read/29134188/simulation-study-of-quantitative-precision-of-the-pet-x-dedicated-breast-pet-scanner
#1
Chengeng Zeng, Paul E Kinahan, Hua Qian, Robert L Harrison, Kyle M Champley, Lawrence R MacDonald
The goal for positron emission tomography (PET)/X is measuring changes in radiotracer uptake for early assessment of response to breast cancer therapy. Upper bounds for detecting such changes were investigated using simulation and two image reconstruction algorithms customized to the PET/X rectangular geometry. Analytical reconstruction was used to study spatial resolution, comparing results with the distance of the closest approach (DCA) resolution surrogate that is independent of the reconstruction method...
October 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/29130074/does-noise-weighting-matter-in-ct-iterative-reconstruction
#2
Gengsheng L Zeng, Wenli Wang
This paper uses a computer simulation to investigate whether a more accurate noise model always results in less noisy images in CT iterative reconstruction. We start with a hypothetic non-realistic noise model for the CT measurements, by assuming that the attenuation coefficient is energy independent and there is no scattering. A variance formula for this model is derived and presented. Based on this model, computer simulations are conducted with 12 different ad hoc noise weighting methods, and their results are compared...
January 2017: IEEE transactions on radiation and plasma medical sciences
https://www.readbyqxmd.com/read/29120665/screening-for-lung-cancer-using-sub-millisievert-chest-ct-with-iterative-reconstruction-algorithm-image-quality-and-nodule-detectability
#3
Zhang Miao, Qi Weiwei, Sun Ye, Jiang Yan, Liu Xiaoyi, Nan Hong
OBJECTIVE: To investigate the image quality and nodules detectability using ultra-low dose (ULD) protocol with iterative model reconstruction (IMR) algorithm when compared to routine low dose (LD) chest CT in lung cancer screening. METHODS: Chest CT scans were acquired using a 256-slice scanner for 300 subjects. The scan protocol for ULD group was 120kVp/17mAs while the LD group was 120kVp/30mAs. All images were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and IMR algorithms...
November 9, 2017: British Journal of Radiology
https://www.readbyqxmd.com/read/29096395/automatic-correction-of-nonlinear-damping-effects-in-haadf-stem-tomography-for-nanomaterials-of-discrete-compositions
#4
Zhichao Zhong, Richard Aveyard, Bernd Rieger, Sara Bals, Willem Jan Palenstijn, K Joost Batenburg
HAADF-STEM tomography is a common technique for characterizing the three-dimensional morphology of nanomaterials. In conventional tomographic reconstruction algorithms, the image intensity is assumed to be a linear projection of a physical property of the specimen. However, this assumption of linearity is not completely valid due to the nonlinear damping of signal intensities. The nonlinear damping effects increase w.r.t the specimen thickness and lead to so-called "cupping artifacts", due to a mismatch with the linear model used in the reconstruction algorithm...
October 30, 2017: Ultramicroscopy
https://www.readbyqxmd.com/read/29073332/numerical-methods-for-polyline-to-point-cloud-registration-with-applications-to-patient-specific-stent-reconstruction
#5
Claire Yilin Lin, Alessandro Veneziani, Lars Ruthotto
We present novel numerical methods for Polyline-to-Point-Cloud Registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling...
October 26, 2017: International Journal for Numerical Methods in Biomedical Engineering
https://www.readbyqxmd.com/read/29067815/diagnostic-performance-of-advanced-modeled-iterative-reconstruction-applied-images-for-detecting-urinary-stones-on-submillisievert-low-dose-computed-tomography
#6
Ju Hee Ahn, Seung Ho Kim, Seung Jin Kim, In Chul Nam, Sung Jae Lee, Seong Yong Pak
Background Repeated computed tomography (CT) scans may be an issue in young adults with urinary stones. Therefore, it is important to know how far the dose can be reduced while maintaining the diagnostic performance. Purpose To generate a hypothesis that it is feasible to decrease the radiation dose to a sub-millisievert (mSv) level with the addition of advanced modeled iterative reconstruction (ADMIRE) while maintaining the sensitivity to standard-dose CT (SDCT) for the detection of urinary stones. Material and Methods Ninety-two consecutive patients with urinary stones underwent non-enhanced CT that consisted of standard (120 kVp, 200 mAs) and lose-dose (LDCT) (80 kVp, 60 mAs)...
January 1, 2017: Acta Radiologica
https://www.readbyqxmd.com/read/29066028/feasibility-study-of-iterative-model-reconstruction-combined-with-low-tube-voltage-low-iodine-load-and-low-iodine-delivery-rate-in-craniocervical-ct-angiography
#7
W Cai, C Hu, S Hu, X Wang, J Gong, W Zhang, D Shi, B Cheng
AIM: To investigate the feasibility of iterative model reconstruction (IMR) combined with low tube voltage, low iodine load, and low iodine deliver rate in craniocervical computed tomography angiography (CTA). MATERIALS AND METHODS: Sixty patients were randomly divided into two groups (n=30 for each): group A: 120 kVp, 50 ml of iopromide at a flow rate of 5 ml/s; filtered back projection (FBP) reconstruction; group B: 80 kVp, 30 ml of iohexol at 4.5 ml/s; hybrid iterative reconstruction (HIR) for group B1 and IMR for group B2...
October 21, 2017: Clinical Radiology
https://www.readbyqxmd.com/read/29058232/iterative-model-reconstruction-imr-algorithm-for-reduced-radiation-dose-renal-artery-ct-angiography-with-different-tube-voltage-protocols
#8
Le Qin, ZePeng Ma, FuHua Yan, WenJie Yang
PURPOSE: To investigate the image quality (IQ) of reduced radiation dose (RRD) renal artery CT angiography (CTA) using iterative model reconstruction (IMR) algorithm at different tube voltage. METHODS: Renal artery CTA scans were acquired with a 256-MDCT scanner on 84 patients assigned into four groups. Group 4 was scanned as standard radiation dose (SRD) group: 120 kVp, automatic tube current modulation (ATCM) technique with an Image Quality Index of 20, and filtered back projection (FBP) algorithm...
October 20, 2017: La Radiologia Medica
https://www.readbyqxmd.com/read/29051681/a-framelet-based-iterative-maximum-likelihood-reconstruction-algorithm-for-spectral-ct
#9
Yingmei Wang, Ge Wang, Shuwei Mao, Wenxiang Cong, Zhilong Ji, Jian-Feng Cai, Yangbo Ye
Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ(r, E)at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis...
November 2016: Inverse Problems
https://www.readbyqxmd.com/read/29046903/fod-restoration-for-enhanced-mapping-of-white-matter-lesion-connectivity
#10
Wei Sun, Lilyana Amezcua, Yonggang Shi
To achieve improved understanding of white matter (WM) lesions and their effect on brain functions, it is important to obtain a comprehensive map of their connectivity. However, changes of the cellular environment in WM lesions attenuate diffusion MRI (dMRI) signals and make the robust estimation of fiber orientation distributions (FODs) difficult. In this work, we integrate techniques from image inpainting and compartment modeling to develop a novel method for enhancing FOD estimation in WM lesions from multi-shell dMRI, which is becoming increasingly popular with the success of the Human Connectome Project (HCP)...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29041567/optical-tomographic-reconstruction-based-on-multi-slice-wave-propagation-method
#11
Xichao Ma, Wen Xiao, Feng Pan
In optical tomography, it is challenging to obtain high-quality results for complex-structured objects which induce multiple scattering. Nonlinear reconstruction methods outperform linear ones in these situations. A promising nonlinear method is the approach based on beam propagation method, but its accuracy may decrease for complicated structures. In this paper, we describe a novel tomographic reconstruction method using multi-slice wave propagation method (WPM) as the forward model, which simulates the scattering process more precisely but has not been introduced in tomographic reconstruction before...
September 18, 2017: Optics Express
https://www.readbyqxmd.com/read/29036139/phase-error-estimation-and-image-reconstruction-from-digital-holography-data-using-a-bayesian-framework
#12
Casey J Pellizzari, Mark F Spencer, Charles A Bouman
The estimation of phase errors from digital-holography data is critical for applications such as imaging or wavefront sensing. Conventional techniques require multiple i.i.d. data and perform poorly in the presence of high noise or large phase errors. In this paper, we propose a method to estimate isoplanatic phase errors from a single data realization. We develop a model-based iterative reconstruction algorithm that computes the maximum a posteriori estimate of the phase and the speckle-free object reflectance...
September 1, 2017: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
https://www.readbyqxmd.com/read/29035215/task-driven-optimization-of-fluence-field-and-regularization-for-model-based-iterative-reconstruction-in-computed-tomography
#13
Grace J Gang, Jeffrey H Siewerdsen, J Webster Stayman
This work presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood (PL) reconstruction that maximizes a taskbased imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index (d0) throughout the image. The optimization algorithm alternates between FFM (represented by lowdimensional basis functions) and local regularization (including the regularization strength and directional penalty weights)...
October 16, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/29028040/ex-vivo-validation-of-photo-magnetic-imaging
#14
Alex Luk, Farouk Nouizi, Hakan Erkol, Mehmet B Unlu, Gultekin Gulsen
We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions...
October 15, 2017: Optics Letters
https://www.readbyqxmd.com/read/29027238/a-deep-convolutional-neural-network-using-directional-wavelets-for-low-dose-x-ray-ct-reconstruction
#15
Eunhee Kang, Junhong Min, Jong Chul Ye
PURPOSE: Due to the potential risk of inducing cancer, radiation exposure by X-ray CT devices should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts typically occur due to photon starvation, beam hardening, and other causes, all of which decrease the reliability of the diagnosis. Thus, a high-quality reconstruction method from low-dose X-ray CT data has become a major research topic in the CT community. Conventional model-based de-noising approaches are, however, computationally very expensive, and image-domain de-noising approaches cannot readily remove CT-specific noise patterns...
October 2017: Medical Physics
https://www.readbyqxmd.com/read/29022741/diagnostic-accuracy-of-in-stent-restenosis-using-model-based-iterative-reconstruction-at-coronary-ct-angiography-initial-experience
#16
Fuminari Tatsugami, Toru Higaki, Hiroaki Sakane, Yuko Nakamura, Makoto Iida, Yasutaka Baba, Chikako Fujioka, Atsuhiro Senoo, Toshiro Kitagawa, Hideya Yamamoto, Yasuki Kihara, Kazuo Awai
OBJECTIVE: The purpose of our study was to compare the diagnostic performance of coronary CT angiography (CTA) subjected to model-based iterative reconstruction (IR) or hybrid IR to rule out coronary in-stent restenosis. METHODS: We enrolled 16 patients who harboured 22 coronary stents. They underwent coronary CTA on a 320-slice CT scanner. The images were reconstructed with hybrid IR (AIDR 3D) and model-based IR (FIRST) algorithms. We calculated the stent lumen attenuation increase ratio and measured the visible stent lumen diameter...
October 27, 2017: British Journal of Radiology
https://www.readbyqxmd.com/read/29019028/application-of-a-full-model-based-iterative-reconstruction-mbir-in-80%C3%A2-kvp-ultra-low-dose-paranasal-sinus-ct-imaging-of-pediatric-patients
#17
Jihang Sun, Qifeng Zhang, Xiaomin Duan, Chengyue Zhang, Pengpeng Wang, Chenguang Jia, Yong Liu, Yun Peng
OBJECTIVE: To evaluate the clinical application of a full model-based iterative reconstruction (MBIR) algorithm in the ultra-low-dose paranasal sinus CT imaging of children. MATERIALS AND METHODS: In the first phase, 16 low-dose CT dacryocystography (DCG) (80 kV/64 mAs) scans were reconstructed with MBIR and filtered back-projection (FBP) to demonstrate noise reduction capability of MBIR. MBIR images were also compared with the images of 21 standard-dose paranasal sinus patients reconstructed with adaptive statistical iterative reconstruction (ASIR) algorithm...
October 10, 2017: La Radiologia Medica
https://www.readbyqxmd.com/read/28994668/correction-of-patient-motion-in-cone-beam-ct-using-3d-2d-registration
#18
Sarah Ouadah, Matthew W Jacobson, Joseph Webster Stayman, Tina Ehtiati, Clifford Raabe Weiss, Jeffrey H Siewerdsen
Cone-beam CT (CBCT) is increasingly common in guidance of interventional procedures but can be subject to artifacts arising from patient motion during fairly long (~5-60s) scan times. We present a fiducial-free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in the intrinsic and extrinsic parameters of geometric calibration. The 3D-2D registration process registers each projection to a prior 3D image by maximizing gradient orientation using the covariance matrix adaptation-evolution strategy (CMA-ES) optimizer...
October 10, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28989990/molecular-breast-imaging-using-synthetic-projections-from-high-purity-germanium-detectors-a-simulation-study
#19
Desmond Campbell, Todd Peterson
High-Purity Germanium (HPGe) gamma cameras are an emerging technology for Molecular Breast Imaging (MBI) due to their 2D lateral spatial resolution, depth-of-interaction (DOI) estimation, and superb energy resolution. In this simulation study, we investigate the potential imaging performance of an opposing view dual-head HPGe breast imaging system using a synthetic-projection technique, which utilizes DOI data with varying degrees of overlap in an iterative OSEM reconstruction algorithm to create 3D images from which new 2D projections are then created...
September 2017: IEEE transactions on radiation and plasma medical sciences
https://www.readbyqxmd.com/read/28987977/robust-alternating-low-rank-representation-by-joint-lp-and-l2-p-norm-minimization
#20
Zhao Zhang, Mingbo Zhao, Fanzhang Li, Li Zhang, Shuicheng Yan
We propose a robust Alternating Low-Rank Representation (ALRR) model formed by an alternating forward-backward representation process. For forward representation, ALRR first recovers the low-rank PCs and random corruptions by an adaptive local Robust PCA (RPCA). Then, ALRR performs a joint Lp-norm and L2,p-norm minimization (0<p <1) based sparse LRR by taking the low-rank PCs as inputs and dictionary instead of using the original noisy data to learn the coding coefficients for subspace recovery, where the Lp-norm on the coefficients can ensure joint sparsity for subspace representation, while the L2,p-norm on the reconstruction error can handle outlier pursuit...
September 14, 2017: Neural Networks: the Official Journal of the International Neural Network Society
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