Accelerated slice encoding for metal artifact correction.

PubMed

Hargreaves, Brian A; Chen, Weitian; Lu, Wenmiao; Alley, Marcus T; Gold, Garry E; Brau, Anja C S; Pauly, John M; Pauly, Kim Butts

2010-04-01

To demonstrate accelerated imaging with both artifact reduction and different contrast mechanisms near metallic implants. Slice-encoding for metal artifact correction (SEMAC) is a modified spin echo sequence that uses view-angle tilting and slice-direction phase encoding to correct both in-plane and through-plane artifacts. Standard spin echo trains and short-TI inversion recovery (STIR) allow efficient PD-weighted imaging with optional fat suppression. A completely linear reconstruction allows incorporation of parallel imaging and partial Fourier imaging. The signal-to-noise ratio (SNR) effects of all reconstructions were quantified in one subject. Ten subjects with different metallic implants were scanned using SEMAC protocols, all with scan times below 11 minutes, as well as with standard spin echo methods. The SNR using standard acceleration techniques is unaffected by the linear SEMAC reconstruction. In all cases with implants, accelerated SEMAC significantly reduced artifacts compared with standard imaging techniques, with no additional artifacts from acceleration techniques. The use of different contrast mechanisms allowed differentiation of fluid from other structures in several subjects. SEMAC imaging can be combined with standard echo-train imaging, parallel imaging, partial-Fourier imaging, and inversion recovery techniques to offer flexible image contrast with a dramatic reduction of metal-induced artifacts in scan times under 11 minutes. (c) 2010 Wiley-Liss, Inc.

GRAPPA reconstructed wave-CAIPI MP-RAGE at 7 Tesla.

PubMed

Schwarz, Jolanda M; Pracht, Eberhard D; Brenner, Daniel; Reuter, Martin; Stöcker, Tony

2018-04-16

The aim of this project was to develop a GRAPPA-based reconstruction for wave-CAIPI data. Wave-CAIPI fully exploits the 3D coil sensitivity variations by combining corkscrew k-space trajectories with CAIPIRINHA sampling. It reduces artifacts and limits reconstruction induced spatially varying noise enhancement. The GRAPPA-based wave-CAIPI method is robust and does not depend on the accuracy of coil sensitivity estimations. We developed a GRAPPA-based, noniterative wave-CAIPI reconstruction algorithm utilizing multiple GRAPPA kernels. For data acquisition, we implemented a fast 3D magnetization-prepared rapid gradient-echo wave-CAIPI sequence tailored for ultra-high field application. The imaging results were evaluated by comparing the g-factor and the root mean square error to Cartesian CAIPIRINHA acquisitions. Additionally, to assess the performance of subcortical segmentations (calculated by FreeSurfer), the data were analyzed across five subjects. Sixteen-fold accelerated whole brain magnetization-prepared rapid gradient-echo data (1 mm isotropic resolution) were acquired in 40 seconds at 7T. A clear improvement in image quality compared to Cartesian CAIPIRINHA sampling was observed. For the chosen imaging protocol, the results of 16-fold accelerated wave-CAIPI acquisitions were comparable to results of 12-fold accelerated Cartesian CAIPIRINHA. In comparison to the originally proposed SENSitivity Encoding reconstruction of Wave-CAIPI data, the GRAPPA approach provided similar image quality. High-quality, wave-CAIPI magnetization-prepared rapid gradient-echo images can be reconstructed by means of a GRAPPA-based reconstruction algorithm. Even for high acceleration factors, the noniterative reconstruction is robust and does not require coil sensitivity estimations. By altering the aliasing pattern, ultra-fast whole-brain structural imaging becomes feasible. © 2018 International Society for Magnetic Resonance in Medicine.

Parallel Reconstruction Using Null Operations (PRUNO)

PubMed Central

Zhang, Jian; Liu, Chunlei; Moseley, Michael E.

2011-01-01

A novel iterative k-space data-driven technique, namely Parallel Reconstruction Using Null Operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data calibration and image reconstruction are formulated into linear algebra problems based on a generalized system model. An optimal data calibration strategy is demonstrated by using Singular Value Decomposition (SVD). And an iterative conjugate- gradient approach is proposed to efficiently solve missing k-space samples during reconstruction. With its generalized formulation and precise mathematical model, PRUNO reconstruction yields good accuracy, flexibility, stability. Both computer simulation and in vivo studies have shown that PRUNO produces much better reconstruction quality than autocalibrating partially parallel acquisition (GRAPPA), especially under high accelerating rates. With the aid of PRUO reconstruction, ultra high accelerating parallel imaging can be performed with decent image quality. For example, we have done successful PRUNO reconstruction at a reduction factor of 6 (effective factor of 4.44) with 8 coils and only a few autocalibration signal (ACS) lines. PMID:21604290

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding.

PubMed

Benkert, Thomas; Tian, Ye; Huang, Chenchan; DiBella, Edward V R; Chandarana, Hersh; Feng, Li

2018-07-01

Golden-angle radial sparse parallel (GRASP) MRI reconstruction requires gridding and regridding to transform data between radial and Cartesian k-space. These operations are repeatedly performed in each iteration, which makes the reconstruction computationally demanding. This work aimed to accelerate GRASP reconstruction using self-calibrating GRAPPA operator gridding (GROG) and to validate its performance in clinical imaging. GROG is an alternative gridding approach based on parallel imaging, in which k-space data acquired on a non-Cartesian grid are shifted onto a Cartesian k-space grid using information from multicoil arrays. For iterative non-Cartesian image reconstruction, GROG is performed only once as a preprocessing step. Therefore, the subsequent iterative reconstruction can be performed directly in Cartesian space, which significantly reduces computational burden. Here, a framework combining GROG with GRASP (GROG-GRASP) is first optimized and then compared with standard GRASP reconstruction in 22 prostate patients. GROG-GRASP achieved approximately 4.2-fold reduction in reconstruction time compared with GRASP (∼333 min versus ∼78 min) while maintaining image quality (structural similarity index ≈ 0.97 and root mean square error ≈ 0.007). Visual image quality assessment by two experienced radiologists did not show significant differences between the two reconstruction schemes. With a graphics processing unit implementation, image reconstruction time can be further reduced to approximately 14 min. The GRASP reconstruction can be substantially accelerated using GROG. This framework is promising toward broader clinical application of GRASP and other iterative non-Cartesian reconstruction methods. Magn Reson Med 80:286-293, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization.

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization

PubMed Central

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate. PMID:27073853

Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm.

PubMed

Angelis, G I; Reader, A J; Markiewicz, P J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2013-08-07

Recent studies have demonstrated the benefits of a resolution model within iterative reconstruction algorithms in an attempt to account for effects that degrade the spatial resolution of the reconstructed images. However, these algorithms suffer from slower convergence rates, compared to algorithms where no resolution model is used, due to the additional need to solve an image deconvolution problem. In this paper, a recently proposed algorithm, which decouples the tomographic and image deconvolution problems within an image-based expectation maximization (EM) framework, was evaluated. This separation is convenient, because more computational effort can be placed on the image deconvolution problem and therefore accelerate convergence. Since the computational cost of solving the image deconvolution problem is relatively small, multiple image-based EM iterations do not significantly increase the overall reconstruction time. The proposed algorithm was evaluated using 2D simulations, as well as measured 3D data acquired on the high-resolution research tomograph. Results showed that bias reduction can be accelerated by interleaving multiple iterations of the image-based EM algorithm solving the resolution model problem, with a single EM iteration solving the tomographic problem. Significant improvements were observed particularly for voxels that were located on the boundaries between regions of high contrast within the object being imaged and for small regions of interest, where resolution recovery is usually more challenging. Minor differences were observed using the proposed nested algorithm, compared to the single iteration normally performed, when an optimal number of iterations are performed for each algorithm. However, using the proposed nested approach convergence is significantly accelerated enabling reconstruction using far fewer tomographic iterations (up to 70% fewer iterations for small regions). Nevertheless, the optimal number of nested image-based EM iterations is hard to be defined and it should be selected according to the given application.

Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction.

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2017-01-01

Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

Efficient parallel reconstruction for high resolution multishot spiral diffusion data with low rank constraint.

PubMed

Liao, Congyu; Chen, Ying; Cao, Xiaozhi; Chen, Song; He, Hongjian; Mani, Merry; Jacob, Mathews; Magnotta, Vincent; Zhong, Jianhui

2017-03-01

To propose a novel reconstruction method using parallel imaging with low rank constraint to accelerate high resolution multishot spiral diffusion imaging. The undersampled high resolution diffusion data were reconstructed based on a low rank (LR) constraint using similarities between the data of different interleaves from a multishot spiral acquisition. The self-navigated phase compensation using the low resolution phase data in the center of k-space was applied to correct shot-to-shot phase variations induced by motion artifacts. The low rank reconstruction was combined with sensitivity encoding (SENSE) for further acceleration. The efficiency of the proposed joint reconstruction framework, dubbed LR-SENSE, was evaluated through error quantifications and compared with ℓ1 regularized compressed sensing method and conventional iterative SENSE method using the same datasets. It was shown that with a same acceleration factor, the proposed LR-SENSE method had the smallest normalized sum-of-squares errors among all the compared methods in all diffusion weighted images and DTI-derived index maps, when evaluated with different acceleration factors (R = 2, 3, 4) and for all the acquired diffusion directions. Robust high resolution diffusion weighted image can be efficiently reconstructed from highly undersampled multishot spiral data with the proposed LR-SENSE method. Magn Reson Med 77:1359-1366, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Reconstruction of multiple-pinhole micro-SPECT data using origin ensembles.

PubMed

Lyon, Morgan C; Sitek, Arkadiusz; Metzler, Scott D; Moore, Stephen C

2016-10-01

The authors are currently developing a dual-resolution multiple-pinhole microSPECT imaging system based on three large NaI(Tl) gamma cameras. Two multiple-pinhole tungsten collimator tubes will be used sequentially for whole-body "scout" imaging of a mouse, followed by high-resolution (hi-res) imaging of an organ of interest, such as the heart or brain. Ideally, the whole-body image will be reconstructed in real time such that data need only be acquired until the area of interest can be visualized well-enough to determine positioning for the hi-res scan. The authors investigated the utility of the origin ensemble (OE) algorithm for online and offline reconstructions of the scout data. This algorithm operates directly in image space, and can provide estimates of image uncertainty, along with reconstructed images. Techniques for accelerating the OE reconstruction were also introduced and evaluated. System matrices were calculated for our 39-pinhole scout collimator design. SPECT projections were simulated for a range of count levels using the MOBY digital mouse phantom. Simulated data were used for a comparison of OE and maximum-likelihood expectation maximization (MLEM) reconstructions. The OE algorithm convergence was evaluated by calculating the total-image entropy and by measuring the counts in a volume-of-interest (VOI) containing the heart. Total-image entropy was also calculated for simulated MOBY data reconstructed using OE with various levels of parallelization. For VOI measurements in the heart, liver, bladder, and soft-tissue, MLEM and OE reconstructed images agreed within 6%. Image entropy converged after ∼2000 iterations of OE, while the counts in the heart converged earlier at ∼200 iterations of OE. An accelerated version of OE completed 1000 iterations in <9 min for a 6.8M count data set, with some loss of image entropy performance, whereas the same dataset required ∼79 min to complete 1000 iterations of conventional OE. A combination of the two methods showed decreased reconstruction time and no loss of performance when compared to conventional OE alone. OE-reconstructed images were found to be quantitatively and qualitatively similar to MLEM, yet OE also provided estimates of image uncertainty. Some acceleration of the reconstruction can be gained through the use of parallel computing. The OE algorithm is useful for reconstructing multiple-pinhole SPECT data and can be easily modified for real-time reconstruction.

Compressed sensing for rapid late gadolinium enhanced imaging of the left atrium: A preliminary study.

PubMed

Kamesh Iyer, Srikant; Tasdizen, Tolga; Burgon, Nathan; Kholmovski, Eugene; Marrouche, Nassir; Adluru, Ganesh; DiBella, Edward

2016-09-01

Current late gadolinium enhancement (LGE) imaging of left atrial (LA) scar or fibrosis is relatively slow and requires 5-15min to acquire an undersampled (R=1.7) 3D navigated dataset. The GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) based parallel imaging method is the current clinical standard for accelerating 3D LGE imaging of the LA and permits an acceleration factor ~R=1.7. Two compressed sensing (CS) methods have been developed to achieve higher acceleration factors: a patch based collaborative filtering technique tested with acceleration factor R~3, and a technique that uses a 3D radial stack-of-stars acquisition pattern (R~1.8) with a 3D total variation constraint. The long reconstruction time of these CS methods makes them unwieldy to use, especially the patch based collaborative filtering technique. In addition, the effect of CS techniques on the quantification of percentage of scar/fibrosis is not known. We sought to develop a practical compressed sensing method for imaging the LA at high acceleration factors. In order to develop a clinically viable method with short reconstruction time, a Split Bregman (SB) reconstruction method with 3D total variation (TV) constraints was developed and implemented. The method was tested on 8 atrial fibrillation patients (4 pre-ablation and 4 post-ablation datasets). Blur metric, normalized mean squared error and peak signal to noise ratio were used as metrics to analyze the quality of the reconstructed images, Quantification of the extent of LGE was performed on the undersampled images and compared with the fully sampled images. Quantification of scar from post-ablation datasets and quantification of fibrosis from pre-ablation datasets showed that acceleration factors up to R~3.5 gave good 3D LGE images of the LA wall, using a 3D TV constraint and constrained SB methods. This corresponds to reducing the scan time by half, compared to currently used GRAPPA methods. Reconstruction of 3D LGE images using the SB method was over 20 times faster than standard gradient descent methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Accelerated acquisition of tagged MRI for cardiac motion correction in simultaneous PET-MR: Phantom and patient studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Chuan, E-mail: chuan.huang@stonybrookmedicine.edu; Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115; Departments of Radiology, Psychiatry, Stony Brook Medicine, Stony Brook, New York 11794

2015-02-15

Purpose: Degradation of image quality caused by cardiac and respiratory motions hampers the diagnostic quality of cardiac PET. It has been shown that improved diagnostic accuracy of myocardial defect can be achieved by tagged MR (tMR) based PET motion correction using simultaneous PET-MR. However, one major hurdle for the adoption of tMR-based PET motion correction in the PET-MR routine is the long acquisition time needed for the collection of fully sampled tMR data. In this work, the authors propose an accelerated tMR acquisition strategy using parallel imaging and/or compressed sensing and assess the impact on the tMR-based motion corrected PETmore » using phantom and patient data. Methods: Fully sampled tMR data were acquired simultaneously with PET list-mode data on two simultaneous PET-MR scanners for a cardiac phantom and a patient. Parallel imaging and compressed sensing were retrospectively performed by GRAPPA and kt-FOCUSS algorithms with various acceleration factors. Motion fields were estimated using nonrigid B-spline image registration from both the accelerated and fully sampled tMR images. The motion fields were incorporated into a motion corrected ordered subset expectation maximization reconstruction algorithm with motion-dependent attenuation correction. Results: Although tMR acceleration introduced image artifacts into the tMR images for both phantom and patient data, motion corrected PET images yielded similar image quality as those obtained using the fully sampled tMR images for low to moderate acceleration factors (<4). Quantitative analysis of myocardial defect contrast over ten independent noise realizations showed similar results. It was further observed that although the image quality of the motion corrected PET images deteriorates for high acceleration factors, the images were still superior to the images reconstructed without motion correction. Conclusions: Accelerated tMR images obtained with more than 4 times acceleration can still provide relatively accurate motion fields and yield tMR-based motion corrected PET images with similar image quality as those reconstructed using fully sampled tMR data. The reduction of tMR acquisition time makes it more compatible with routine clinical cardiac PET-MR studies.« less

3D single point imaging with compressed sensing provides high temporal resolution R 2* mapping for in vivo preclinical applications.

PubMed

Rioux, James A; Beyea, Steven D; Bowen, Chris V

2017-02-01

Purely phase-encoded techniques such as single point imaging (SPI) are generally unsuitable for in vivo imaging due to lengthy acquisition times. Reconstruction of highly undersampled data using compressed sensing allows SPI data to be quickly obtained from animal models, enabling applications in preclinical cellular and molecular imaging. TurboSPI is a multi-echo single point technique that acquires hundreds of images with microsecond spacing, enabling high temporal resolution relaxometry of large-R 2 * systems such as iron-loaded cells. TurboSPI acquisitions can be pseudo-randomly undersampled in all three dimensions to increase artifact incoherence, and can provide prior information to improve reconstruction. We evaluated the performance of CS-TurboSPI in phantoms, a rat ex vivo, and a mouse in vivo. An algorithm for iterative reconstruction of TurboSPI relaxometry time courses does not affect image quality or R 2 * mapping in vitro at acceleration factors up to 10. Imaging ex vivo is possible at similar acceleration factors, and in vivo imaging is demonstrated at an acceleration factor of 8, such that acquisition time is under 1 h. Accelerated TurboSPI enables preclinical R 2 * mapping without loss of data quality, and may show increased specificity to iron oxide compared to other sequences.

NOTE: Acceleration of Monte Carlo-based scatter compensation for cardiac SPECT

NASA Astrophysics Data System (ADS)

Sohlberg, A.; Watabe, H.; Iida, H.

2008-07-01

Single proton emission computed tomography (SPECT) images are degraded by photon scatter making scatter compensation essential for accurate reconstruction. Reconstruction-based scatter compensation with Monte Carlo (MC) modelling of scatter shows promise for accurate scatter correction, but it is normally hampered by long computation times. The aim of this work was to accelerate the MC-based scatter compensation using coarse grid and intermittent scatter modelling. The acceleration methods were compared to un-accelerated implementation using MC-simulated projection data of the mathematical cardiac torso (MCAT) phantom modelling 99mTc uptake and clinical myocardial perfusion studies. The results showed that when combined the acceleration methods reduced the reconstruction time for 10 ordered subset expectation maximization (OS-EM) iterations from 56 to 11 min without a significant reduction in image quality indicating that the coarse grid and intermittent scatter modelling are suitable for MC-based scatter compensation in cardiac SPECT.

Accelerating non-contrast-enhanced MR angiography with inflow inversion recovery imaging by skipped phase encoding and edge deghosting (SPEED).

PubMed

Chang, Zheng; Xiang, Qing-San; Shen, Hao; Yin, Fang-Fang

2010-03-01

To accelerate non-contrast-enhanced MR angiography (MRA) with inflow inversion recovery (IFIR) with a fast imaging method, Skipped Phase Encoding and Edge Deghosting (SPEED). IFIR imaging uses a preparatory inversion pulse to reduce signals from static tissue, while leaving inflow arterial blood unaffected, resulting in sparse arterial vasculature on modest tissue background. By taking advantage of vascular sparsity, SPEED can be simplified with a single-layer model to achieve higher efficiency in both scan time reduction and image reconstruction. SPEED can also make use of information available in multiple coils for further acceleration. The techniques are demonstrated with a three-dimensional renal non-contrast-enhanced IFIR MRA study. Images are reconstructed by SPEED based on a single-layer model to achieve an undersampling factor of up to 2.5 using one skipped phase encoding direction. By making use of information available in multiple coils, SPEED can achieve an undersampling factor of up to 8.3 with four receiver coils. The reconstructed images generally have comparable quality as that of the reference images reconstructed from full k-space data. As demonstrated with a three-dimensional renal IFIR scan, SPEED based on a single-layer model is able to reduce scan time further and achieve higher computational efficiency than the original SPEED.

Comparison of image deconvolution algorithms on simulated and laboratory infrared images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Proctor, D.

1994-11-15

We compare Maximum Likelihood, Maximum Entropy, Accelerated Lucy-Richardson, Weighted Goodness of Fit, and Pixon reconstructions of simple scenes as a function of signal-to-noise ratio for simulated images with randomly generated noise. Reconstruction results of infrared images taken with the TAISIR (Temperature and Imaging System InfraRed) are also discussed.

Incorporation of Prior Knowledge of Signal Behavior Into the Reconstruction to Accelerate the Acquisition of Diffusion MRI Data.

PubMed

Abascal, Juan F P J; Desco, Manuel; Parra-Robles, Juan

2018-02-01

Diffusion MRI data are generally acquired using hyperpolarized gases during patient breath-hold, which yields a compromise between achievable image resolution, lung coverage, and number of -values. In this paper, we propose a novel method that accelerates the acquisition of diffusion MRI data by undersampling in both the spatial and -value dimensions and incorporating knowledge about signal decay into the reconstruction (SIDER). SIDER is compared with total variation (TV) reconstruction by assessing its effect on both the recovery of ventilation images and the estimated mean alveolar dimensions (MADs). Both methods are assessed by retrospectively undersampling diffusion data sets ( =8) of healthy volunteers and patients with Chronic Obstructive Pulmonary Disease (COPD) for acceleration factors between x2 and x10. TV led to large errors and artifacts for acceleration factors equal to or larger than x5. SIDER improved TV, with a lower solution error and MAD histograms closer to those obtained from fully sampled data for acceleration factors up to x10. SIDER preserved image quality at all acceleration factors, although images were slightly smoothed and some details were lost at x10. In conclusion, we developed and validated a novel compressed sensing method for lung MRI imaging and achieved high acceleration factors, which can be used to increase the amount of data acquired during breath-hold. This methodology is expected to improve the accuracy of estimated lung microstructure dimensions and provide more options in the study of lung diseases with MRI.

Accelerated Compressed Sensing Based CT Image Reconstruction.

PubMed

Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

2015-01-01

In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

Accelerated Compressed Sensing Based CT Image Reconstruction

PubMed Central

Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R.; Paul, Narinder S.; Cobbold, Richard S. C.

2015-01-01

In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200

Parallel MR Imaging with Accelerations Beyond the Number of Receiver Channels Using Real Image Reconstruction.

PubMed

Ji, Jim; Wright, Steven

2005-01-01

Parallel imaging using multiple phased-array coils and receiver channels has become an effective approach to high-speed magnetic resonance imaging (MRI). To obtain high spatiotemporal resolution, the k-space is subsampled and later interpolated using multiple channel data. Higher subsampling factors result in faster image acquisition. However, the subsampling factors are upper-bounded by the number of parallel channels. Phase constraints have been previously proposed to overcome this limitation with some success. In this paper, we demonstrate that in certain applications it is possible to obtain acceleration factors potentially up to twice the channel numbers by using a real image constraint. Data acquisition and processing methods to manipulate and estimate of the image phase information are presented for improving image reconstruction. In-vivo brain MRI experimental results show that accelerations up to 6 are feasible with 4-channel data.

Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI

PubMed Central

Kamesh Iyer, Srikant; Tasdizen, Tolga; Likhite, Devavrat; DiBella, Edward

2016-01-01

Purpose: Rapid reconstruction of undersampled multicoil MRI data with iterative constrained reconstruction method is a challenge. The authors sought to develop a new substitution based variable splitting algorithm for faster reconstruction of multicoil cardiac perfusion MRI data. Methods: The new method, split Bregman multicoil accelerated reconstruction technique (SMART), uses a combination of split Bregman based variable splitting and iterative reweighting techniques to achieve fast convergence. Total variation constraints are used along the spatial and temporal dimensions. The method is tested on nine ECG-gated dog perfusion datasets, acquired with a 30-ray golden ratio radial sampling pattern and ten ungated human perfusion datasets, acquired with a 24-ray golden ratio radial sampling pattern. Image quality and reconstruction speed are evaluated and compared to a gradient descent (GD) implementation and to multicoil k-t SLR, a reconstruction technique that uses a combination of sparsity and low rank constraints. Results: Comparisons based on blur metric and visual inspection showed that SMART images had lower blur and better texture as compared to the GD implementation. On average, the GD based images had an ∼18% higher blur metric as compared to SMART images. Reconstruction of dynamic contrast enhanced (DCE) cardiac perfusion images using the SMART method was ∼6 times faster than standard gradient descent methods. k-t SLR and SMART produced images with comparable image quality, though SMART was ∼6.8 times faster than k-t SLR. Conclusions: The SMART method is a promising approach to reconstruct good quality multicoil images from undersampled DCE cardiac perfusion data rapidly. PMID:27036592

Accelerated High-Dimensional MR Imaging with Sparse Sampling Using Low-Rank Tensors

PubMed Central

He, Jingfei; Liu, Qiegen; Christodoulou, Anthony G.; Ma, Chao; Lam, Fan

2017-01-01

High-dimensional MR imaging often requires long data acquisition time, thereby limiting its practical applications. This paper presents a low-rank tensor based method for accelerated high-dimensional MR imaging using sparse sampling. This method represents high-dimensional images as low-rank tensors (or partially separable functions) and uses this mathematical structure for sparse sampling of the data space and for image reconstruction from highly undersampled data. More specifically, the proposed method acquires two datasets with complementary sampling patterns, one for subspace estimation and the other for image reconstruction; image reconstruction from highly undersampled data is accomplished by fitting the measured data with a sparsity constraint on the core tensor and a group sparsity constraint on the spatial coefficients jointly using the alternating direction method of multipliers. The usefulness of the proposed method is demonstrated in MRI applications; it may also have applications beyond MRI. PMID:27093543

Review of advanced catheter technologies in radiation oncology brachytherapy procedures

PubMed Central

Zhou, Jun; Zamdborg, Leonid; Sebastian, Evelyn

2015-01-01

The development of new catheter and applicator technologies in recent years has significantly improved treatment accuracy, efficiency, and outcomes in brachytherapy. In this paper, we review these advances, focusing on the performance of catheter imaging and reconstruction techniques in brachytherapy procedures using magnetic resonance images and electromagnetic tracking. The accuracy of catheter reconstruction, imaging artifacts, and other notable properties of plastic and titanium applicators in gynecologic treatments are reviewed. The accuracy, noise performance, and limitations of electromagnetic tracking for catheter reconstruction are discussed. Several newly developed applicators for accelerated partial breast irradiation and gynecologic treatments are also reviewed. New hypofractionated high dose rate treatment schemes in prostate cancer and accelerated partial breast irradiation are presented. PMID:26203277

Accelerating Sequences in the Presence of Metal by Exploiting the Spatial Distribution of Off-Resonance

PubMed Central

Smith, Matthew R.; Artz, Nathan S.; Koch, Kevin M.; Samsonov, Alexey; Reeder, Scott B.

2014-01-01

Purpose To demonstrate feasibility of exploiting the spatial distribution of off-resonance surrounding metallic implants for accelerating multispectral imaging techniques. Theory Multispectral imaging (MSI) techniques perform time-consuming independent 3D acquisitions with varying RF frequency offsets to address the extreme off-resonance from metallic implants. Each off-resonance bin provides a unique spatial sensitivity that is analogous to the sensitivity of a receiver coil, and therefore provides a unique opportunity for acceleration. Methods Fully sampled MSI was performed to demonstrate retrospective acceleration. A uniform sampling pattern across off-resonance bins was compared to several adaptive sampling strategies using a total hip replacement phantom. Monte Carlo simulations were performed to compare noise propagation of two of these strategies. With a total knee replacement phantom, positive and negative off-resonance bins were strategically sampled with respect to the B0 field to minimize aliasing. Reconstructions were performed with a parallel imaging framework to demonstrate retrospective acceleration. Results An adaptive sampling scheme dramatically improved reconstruction quality, which was supported by the noise propagation analysis. Independent acceleration of negative and positive off-resonance bins demonstrated reduced overlapping of aliased signal to improve the reconstruction. Conclusion This work presents the feasibility of acceleration in the presence of metal by exploiting the spatial sensitivities of off-resonance bins. PMID:24431210

Joint MR-PET reconstruction using a multi-channel image regularizer

PubMed Central

Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

2016-01-01

While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy. PMID:28055827

Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE)

PubMed Central

Sharif, Behzad; Derbyshire, J. Andrew; Faranesh, Anthony Z.; Bresler, Yoram

2010-01-01

MR imaging of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional non-gated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly-accelerated non-gated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically-driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient-adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject’s heart-rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high resolution non-gated cardiac MRI during a short breath-hold. PMID:20665794

Optimizing convergence rates of alternating minimization reconstruction algorithms for real-time explosive detection applications

NASA Astrophysics Data System (ADS)

Bosch, Carl; Degirmenci, Soysal; Barlow, Jason; Mesika, Assaf; Politte, David G.; O'Sullivan, Joseph A.

2016-05-01

X-ray computed tomography reconstruction for medical, security and industrial applications has evolved through 40 years of experience with rotating gantry scanners using analytic reconstruction techniques such as filtered back projection (FBP). In parallel, research into statistical iterative reconstruction algorithms has evolved to apply to sparse view scanners in nuclear medicine, low data rate scanners in Positron Emission Tomography (PET) [5, 7, 10] and more recently to reduce exposure to ionizing radiation in conventional X-ray CT scanners. Multiple approaches to statistical iterative reconstruction have been developed based primarily on variations of expectation maximization (EM) algorithms. The primary benefit of EM algorithms is the guarantee of convergence that is maintained when iterative corrections are made within the limits of convergent algorithms. The primary disadvantage, however is that strict adherence to correction limits of convergent algorithms extends the number of iterations and ultimate timeline to complete a 3D volumetric reconstruction. Researchers have studied methods to accelerate convergence through more aggressive corrections [1], ordered subsets [1, 3, 4, 9] and spatially variant image updates. In this paper we describe the development of an AM reconstruction algorithm with accelerated convergence for use in a real-time explosive detection application for aviation security. By judiciously applying multiple acceleration techniques and advanced GPU processing architectures, we are able to perform 3D reconstruction of scanned passenger baggage at a rate of 75 slices per second. Analysis of the results on stream of commerce passenger bags demonstrates accelerated convergence by factors of 8 to 15, when comparing images from accelerated and strictly convergent algorithms.

Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression.

PubMed

Dong, Zijing; Wang, Fuyixue; Ma, Xiaodong; Zhang, Zhe; Dai, Erpeng; Yuan, Chun; Guo, Hua

2018-03-01

To develop a novel diffusion imaging reconstruction framework based on iterative self-consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with computation acceleration by virtual coil compression. As a general approach for autocalibrating parallel imaging, SPIRiT improves the performance of traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) methods in that the formulation with self-consistency is better conditioned, suggesting SPIRiT to be a better candidate in k-space-based reconstruction. In this study, a general SPIRiT framework is adopted to incorporate both coil sensitivity and phase variation information as virtual coils and then is applied to 2D navigated iEPI diffusion imaging. To reduce the reconstruction time when using a large number of coils and shots, a novel shot-coil compression method is proposed for computation acceleration in Cartesian sampling. Simulations and in vivo experiments were conducted to evaluate the performance of the proposed method. Compared with the conventional coil compression, the shot-coil compression achieved higher compression rates with reduced errors. The simulation and in vivo experiments demonstrate that the SPIRiT-based reconstruction outperformed the existing method, realigned GRAPPA, and provided superior images with reduced artifacts. The SPIRiT-based reconstruction with virtual coil compression is a reliable method for high-resolution iEPI diffusion imaging. Magn Reson Med 79:1525-1531, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

GPU-accelerated compressed-sensing (CS) image reconstruction in chest digital tomosynthesis (CDT) using CUDA programming

NASA Astrophysics Data System (ADS)

Choi, Sunghoon; Lee, Haenghwa; Lee, Donghoon; Choi, Seungyeon; Shin, Jungwook; Jang, Woojin; Seo, Chang-Woo; Kim, Hee-Joung

2017-03-01

A compressed-sensing (CS) technique has been rapidly applied in medical imaging field for retrieving volumetric data from highly under-sampled projections. Among many variant forms, CS technique based on a total-variation (TV) regularization strategy shows fairly reasonable results in cone-beam geometry. In this study, we implemented the TV-based CS image reconstruction strategy in our prototype chest digital tomosynthesis (CDT) R/F system. Due to the iterative nature of time consuming processes in solving a cost function, we took advantage of parallel computing using graphics processing units (GPU) by the compute unified device architecture (CUDA) programming to accelerate our algorithm. In order to compare the algorithmic performance of our proposed CS algorithm, conventional filtered back-projection (FBP) and simultaneous algebraic reconstruction technique (SART) reconstruction schemes were also studied. The results indicated that the CS produced better contrast-to-noise ratios (CNRs) in the physical phantom images (Teflon region-of-interest) by factors of 3.91 and 1.93 than FBP and SART images, respectively. The resulted human chest phantom images including lung nodules with different diameters also showed better visual appearance in the CS images. Our proposed GPU-accelerated CS reconstruction scheme could produce volumetric data up to 80 times than CPU programming. Total elapsed time for producing 50 coronal planes with 1024×1024 image matrix using 41 projection views were 216.74 seconds for proposed CS algorithms on our GPU programming, which could match the clinically feasible time ( 3 min). Consequently, our results demonstrated that the proposed CS method showed a potential of additional dose reduction in digital tomosynthesis with reasonable image quality in a fast time.

Accelerated T1ρ acquisition for knee cartilage quantification using compressed sensing and data-driven parallel imaging: A feasibility study.

PubMed

Pandit, Prachi; Rivoire, Julien; King, Kevin; Li, Xiaojuan

2016-03-01

Quantitative T1ρ imaging is beneficial for early detection for osteoarthritis but has seen limited clinical use due to long scan times. In this study, we evaluated the feasibility of accelerated T1ρ mapping for knee cartilage quantification using a combination of compressed sensing (CS) and data-driven parallel imaging (ARC-Autocalibrating Reconstruction for Cartesian sampling). A sequential combination of ARC and CS, both during data acquisition and reconstruction, was used to accelerate the acquisition of T1ρ maps. Phantom, ex vivo (porcine knee), and in vivo (human knee) imaging was performed on a GE 3T MR750 scanner. T1ρ quantification after CS-accelerated acquisition was compared with non CS-accelerated acquisition for various cartilage compartments. Accelerating image acquisition using CS did not introduce major deviations in quantification. The coefficient of variation for the root mean squared error increased with increasing acceleration, but for in vivo measurements, it stayed under 5% for a net acceleration factor up to 2, where the acquisition was 25% faster than the reference (only ARC). To the best of our knowledge, this is the first implementation of CS for in vivo T1ρ quantification. These early results show that this technique holds great promise in making quantitative imaging techniques more accessible for clinical applications. © 2015 Wiley Periodicals, Inc.

SU-F-BRCD-09: Total Variation (TV) Based Fast Convergent Iterative CBCT Reconstruction with GPU Acceleration.

PubMed

Xu, Q; Yang, D; Tan, J; Anastasio, M

2012-06-01

To improve image quality and reduce imaging dose in CBCT for radiation therapy applications and to realize near real-time image reconstruction based on use of a fast convergence iterative algorithm and acceleration by multi-GPUs. An iterative image reconstruction that sought to minimize a weighted least squares cost function that employed total variation (TV) regularization was employed to mitigate projection data incompleteness and noise. To achieve rapid 3D image reconstruction (< 1 min), a highly optimized multiple-GPU implementation of the algorithm was developed. The convergence rate and reconstruction accuracy were evaluated using a modified 3D Shepp-Logan digital phantom and a Catphan-600 physical phantom. The reconstructed images were compared with the clinical FDK reconstruction results. Digital phantom studies showed that only 15 iterations and 60 iterations are needed to achieve algorithm convergence for 360-view and 60-view cases, respectively. The RMSE was reduced to 10-4 and 10-2, respectively, by using 15 iterations for each case. Our algorithm required 5.4s to complete one iteration for the 60-view case using one Tesla C2075 GPU. The few-view study indicated that our iterative algorithm has great potential to reduce the imaging dose and preserve good image quality. For the physical Catphan studies, the images obtained from the iterative algorithm possessed better spatial resolution and higher SNRs than those obtained from by use of a clinical FDK reconstruction algorithm. We have developed a fast convergence iterative algorithm for CBCT image reconstruction. The developed algorithm yielded images with better spatial resolution and higher SNR than those produced by a commercial FDK tool. In addition, from the few-view study, the iterative algorithm has shown great potential for significantly reducing imaging dose. We expect that the developed reconstruction approach will facilitate applications including IGART and patient daily CBCT-based treatment localization. © 2012 American Association of Physicists in Medicine.

Monte Carlo-based fluorescence molecular tomography reconstruction method accelerated by a cluster of graphic processing units.

PubMed

Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming

2011-02-01

High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation.

PubMed

Iqbal, Zohaib; Wilson, Neil E; Thomas, M Albert

2017-07-24

1 H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.

Accelerating acquisition strategies for low-frequency conductivity imaging using MREIT

NASA Astrophysics Data System (ADS)

Song, Yizhuang; Seo, Jin Keun; Chauhan, Munish; Indahlastari, Aprinda; Ashok Kumar, Neeta; Sadleir, Rosalind

2018-02-01

We sought to improve efficiency of magnetic resonance electrical impedance tomography data acquisition so that fast conductivity changes or electric field variations could be monitored. Undersampling of k-space was used to decrease acquisition times in spin-echo-based sequences by a factor of two. Full MREIT data were reconstructed using continuity assumptions and preliminary scans gathered without current. We found that phase data were reconstructed faithfully from undersampled data. Conductivity reconstructions of phantom data were also possible. Therefore, undersampled k-space methods can potentially be used to accelerate MREIT acquisition. This method could be an advantage in imaging real-time conductivity changes with MREIT.

Undersampling strategies for compressed sensing accelerated MR spectroscopic imaging

NASA Astrophysics Data System (ADS)

Vidya Shankar, Rohini; Hu, Houchun Harry; Bikkamane Jayadev, Nutandev; Chang, John C.; Kodibagkar, Vikram D.

2017-03-01

Compressed sensing (CS) can accelerate magnetic resonance spectroscopic imaging (MRSI), facilitating its widespread clinical integration. The objective of this study was to assess the effect of different undersampling strategy on CS-MRSI reconstruction quality. Phantom data were acquired on a Philips 3 T Ingenia scanner. Four types of undersampling masks, corresponding to each strategy, namely, low resolution, variable density, iterative design, and a priori were simulated in Matlab and retrospectively applied to the test 1X MRSI data to generate undersampled datasets corresponding to the 2X - 5X, and 7X accelerations for each type of mask. Reconstruction parameters were kept the same in each case(all masks and accelerations) to ensure that any resulting differences can be attributed to the type of mask being employed. The reconstructed datasets from each mask were statistically compared with the reference 1X, and assessed using metrics like the root mean square error and metabolite ratios. Simulation results indicate that both the a priori and variable density undersampling masks maintain high fidelity with the 1X up to five-fold acceleration. The low resolution mask based reconstructions showed statistically significant differences from the 1X with the reconstruction failing at 3X, while the iterative design reconstructions maintained fidelity with the 1X till 4X acceleration. In summary, a pilot study was conducted to identify an optimal sampling mask in CS-MRSI. Simulation results demonstrate that the a priori and variable density masks can provide statistically similar results to the fully sampled reference. Future work would involve implementing these two masks prospectively on a clinical scanner.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

NASA Astrophysics Data System (ADS)

Nouizi, F.; Erkol, H.; Luk, A.; Marks, M.; Unlu, M. B.; Gulsen, G.

2016-10-01

We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

Fast implementations of reconstruction-based scatter compensation in fully 3D SPECT image reconstruction

NASA Astrophysics Data System (ADS)

Kadrmas, Dan J.; Frey, Eric C.; Karimi, Seemeen S.; Tsui, Benjamin M. W.

1998-04-01

Accurate scatter compensation in SPECT can be performed by modelling the scatter response function during the reconstruction process. This method is called reconstruction-based scatter compensation (RBSC). It has been shown that RBSC has a number of advantages over other methods of compensating for scatter, but using RBSC for fully 3D compensation has resulted in prohibitively long reconstruction times. In this work we propose two new methods that can be used in conjunction with existing methods to achieve marked reductions in RBSC reconstruction times. The first method, coarse-grid scatter modelling, significantly accelerates the scatter model by exploiting the fact that scatter is dominated by low-frequency information. The second method, intermittent RBSC, further accelerates the reconstruction process by limiting the number of iterations during which scatter is modelled. The fast implementations were evaluated using a Monte Carlo simulated experiment of the 3D MCAT phantom with tracer, and also using experimentally acquired data with tracer. Results indicated that these fast methods can reconstruct, with fully 3D compensation, images very similar to those obtained using standard RBSC methods, and in reconstruction times that are an order of magnitude shorter. Using these methods, fully 3D iterative reconstruction with RBSC can be performed well within the realm of clinically realistic times (under 10 minutes for image reconstruction).

A survey of GPU-based acceleration techniques in MRI reconstructions

PubMed Central

Wang, Haifeng; Peng, Hanchuan; Chang, Yuchou

2018-01-01

Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community. PMID:29675361

A survey of GPU-based acceleration techniques in MRI reconstructions.

PubMed

Wang, Haifeng; Peng, Hanchuan; Chang, Yuchou; Liang, Dong

2018-03-01

Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community.

Denoising Sparse Images from GRAPPA using the Nullspace Method (DESIGN)

PubMed Central

Weller, Daniel S.; Polimeni, Jonathan R.; Grady, Leo; Wald, Lawrence L.; Adalsteinsson, Elfar; Goyal, Vivek K

2011-01-01

To accelerate magnetic resonance imaging using uniformly undersampled (nonrandom) parallel imaging beyond what is achievable with GRAPPA alone, the Denoising of Sparse Images from GRAPPA using the Nullspace method (DESIGN) is developed. The trade-off between denoising and smoothing the GRAPPA solution is studied for different levels of acceleration. Several brain images reconstructed from uniformly undersampled k-space data using DESIGN are compared against reconstructions using existing methods in terms of difference images (a qualitative measure), PSNR, and noise amplification (g-factors) as measured using the pseudo-multiple replica method. Effects of smoothing, including contrast loss, are studied in synthetic phantom data. In the experiments presented, the contrast loss and spatial resolution are competitive with existing methods. Results for several brain images demonstrate significant improvements over GRAPPA at high acceleration factors in denoising performance with limited blurring or smoothing artifacts. In addition, the measured g-factors suggest that DESIGN mitigates noise amplification better than both GRAPPA and L1 SPIR-iT (the latter limited here by uniform undersampling). PMID:22213069

Wave-CAIPI ViSTa: highly accelerated whole-brain direct myelin water imaging with zero-padding reconstruction.

PubMed

Wu, Zhe; Bilgic, Berkin; He, Hongjian; Tong, Qiqi; Sun, Yi; Du, Yiping; Setsompop, Kawin; Zhong, Jianhui

2018-09-01

This study introduces a highly accelerated whole-brain direct visualization of short transverse relaxation time component (ViSTa) imaging using a wave controlled aliasing in parallel imaging (CAIPI) technique, for acquisition within a clinically acceptable scan time, with the preservation of high image quality and sufficient spatial resolution, and reduced residual point spread function artifacts. Double inversion RF pulses were applied to preserve the signal from short T 1 components for directly extracting myelin water signal in ViSTa imaging. A 2D simultaneous multislice and a 3D acquisition of ViSTa images incorporating wave-encoding were used for data acquisition. Improvements brought by a zero-padding method in wave-CAIPI reconstruction were also investigated. The zero-padding method in wave-CAIPI reconstruction reduced the root-mean-square errors between the wave-encoded and Cartesian gradient echoes for all wave gradient configurations in simulation, and reduced the side-main lobe intensity ratio from 34.5 to 16% in the thin-slab in vivo ViSTa images. In a 4 × acceleration simultaneous-multislice scenario, wave-CAIPI ViSTa achieved negligible g-factors (g mean /g max  = 1.03/1.10), while retaining minimal interslice artifacts. An 8 × accelerated acquisition of 3D wave-CAIPI ViSTa imaging covering the whole brain with 1.1 × 1.1 × 3 mm 3 voxel size was achieved within 15 minutes, and only incurred a small g-factor penalty (g mean /g max  = 1.05/1.16). Whole-brain ViSTa images were obtained within 15 minutes with negligible g-factor penalty by using wave-CAIPI acquisition and zero-padding reconstruction. The proposed zero-padding method was shown to be effective in reducing residual point spread function for wave-encoded images, particularly for ViSTa. © 2018 International Society for Magnetic Resonance in Medicine.

Accelerating separable footprint (SF) forward and back projection on GPU

NASA Astrophysics Data System (ADS)

Xie, Xiaobin; McGaffin, Madison G.; Long, Yong; Fessler, Jeffrey A.; Wen, Minhua; Lin, James

2017-03-01

Statistical image reconstruction (SIR) methods for X-ray CT can improve image quality and reduce radiation dosages over conventional reconstruction methods, such as filtered back projection (FBP). However, SIR methods require much longer computation time. The separable footprint (SF) forward and back projection technique simplifies the calculation of intersecting volumes of image voxels and finite-size beams in a way that is both accurate and efficient for parallel implementation. We propose a new method to accelerate the SF forward and back projection on GPU with NVIDIA's CUDA environment. For the forward projection, we parallelize over all detector cells. For the back projection, we parallelize over all 3D image voxels. The simulation results show that the proposed method is faster than the acceleration method of the SF projectors proposed by Wu and Fessler.13 We further accelerate the proposed method using multiple GPUs. The results show that the computation time is reduced approximately proportional to the number of GPUs.

High resolution human diffusion tensor imaging using 2-D navigated multi-shot SENSE EPI at 7 Tesla

PubMed Central

Jeong, Ha-Kyu; Gore, John C.; Anderson, Adam W.

2012-01-01

The combination of parallel imaging with partial Fourier acquisition has greatly improved the performance of diffusion-weighted single-shot EPI and is the preferred method for acquisitions at low to medium magnetic field strength such as 1.5 or 3 Tesla. Increased off-resonance effects and reduced transverse relaxation times at 7 Tesla, however, generate more significant artifacts than at lower magnetic field strength and limit data acquisition. Additional acceleration of k-space traversal using a multi-shot approach, which acquires a subset of k-space data after each excitation, reduces these artifacts relative to conventional single-shot acquisitions. However, corrections for motion-induced phase errors are not straightforward in accelerated, diffusion-weighted multi-shot EPI because of phase aliasing. In this study, we introduce a simple acquisition and corresponding reconstruction method for diffusion-weighted multi-shot EPI with parallel imaging suitable for use at high field. The reconstruction uses a simple modification of the standard SENSE algorithm to account for shot-to-shot phase errors; the method is called Image Reconstruction using Image-space Sampling functions (IRIS). Using this approach, reconstruction from highly aliased in vivo image data using 2-D navigator phase information is demonstrated for human diffusion-weighted imaging studies at 7 Tesla. The final reconstructed images show submillimeter in-plane resolution with no ghosts and much reduced blurring and off-resonance artifacts. PMID:22592941

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PubMed

Velikina, Julia V; Samsonov, Alexey A

2015-11-01

To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. © 2014 Wiley Periodicals, Inc.

RECONSTRUCTION OF DYNAMIC IMAGE SERIES FROM UNDERSAMPLED MRI DATA USING DATA-DRIVEN MODEL CONSISTENCY CONDITION (MOCCO)

PubMed Central

Velikina, Julia V.; Samsonov, Alexey A.

2014-01-01

Purpose To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models pre-estimated from training data. Theory We introduce the MOdel Consistency COndition (MOCCO) technique that utilizes temporal models to regularize the reconstruction without constraining the solution to be low-rank as performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Methods Our method was compared to standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE MRA) and cardiac CINE imaging. We studied sensitivity of all methods to rank-reduction and temporal subspace modeling errors. Results MOCCO demonstrated reduced sensitivity to modeling errors compared to the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. Conclusions MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. PMID:25399724

Accelerated Fast Spin-Echo Magnetic Resonance Imaging of the Heart Using a Self-Calibrated Split-Echo Approach

PubMed Central

Klix, Sabrina; Hezel, Fabian; Fuchs, Katharina; Ruff, Jan; Dieringer, Matthias A.; Niendorf, Thoralf

2014-01-01

Purpose Design, validation and application of an accelerated fast spin-echo (FSE) variant that uses a split-echo approach for self-calibrated parallel imaging. Methods For self-calibrated, split-echo FSE (SCSE-FSE), extra displacement gradients were incorporated into FSE to decompose odd and even echo groups which were independently phase encoded to derive coil sensitivity maps, and to generate undersampled data (reduction factor up to R = 3). Reference and undersampled data were acquired simultaneously. SENSE reconstruction was employed. Results The feasibility of SCSE-FSE was demonstrated in phantom studies. Point spread function performance of SCSE-FSE was found to be competitive with traditional FSE variants. The immunity of SCSE-FSE for motion induced mis-registration between reference and undersampled data was shown using a dynamic left ventricular model and cardiac imaging. The applicability of black blood prepared SCSE-FSE for cardiac imaging was demonstrated in healthy volunteers including accelerated multi-slice per breath-hold imaging and accelerated high spatial resolution imaging. Conclusion SCSE-FSE obviates the need of external reference scans for SENSE reconstructed parallel imaging with FSE. SCSE-FSE reduces the risk for mis-registration between reference scans and accelerated acquisitions. SCSE-FSE is feasible for imaging of the heart and of large cardiac vessels but also meets the needs of brain, abdominal and liver imaging. PMID:24728341

High Spatial and Temporal Resolution Dynamic Contrast-Enhanced Magnetic Resonance Angiography (CE-MRA) using Compressed Sensing with Magnitude Image Subtraction

PubMed Central

Rapacchi, Stanislas; Han, Fei; Natsuaki, Yutaka; Kroeker, Randall; Plotnik, Adam; Lehman, Evan; Sayre, James; Laub, Gerhard; Finn, J Paul; Hu, Peng

2014-01-01

Purpose We propose a compressed-sensing (CS) technique based on magnitude image subtraction for high spatial and temporal resolution dynamic contrast-enhanced MR angiography (CE-MRA). Methods Our technique integrates the magnitude difference image into the CS reconstruction to promote subtraction sparsity. Fully sampled Cartesian 3D CE-MRA datasets from 6 volunteers were retrospectively under-sampled and three reconstruction strategies were evaluated: k-space subtraction CS, independent CS, and magnitude subtraction CS. The techniques were compared in image quality (vessel delineation, image artifacts, and noise) and image reconstruction error. Our CS technique was further tested on 7 volunteers using a prospectively under-sampled CE-MRA sequence. Results Compared with k-space subtraction and independent CS, our magnitude subtraction CS provides significantly better vessel delineation and less noise at 4X acceleration, and significantly less reconstruction error at 4X and 8X (p<0.05 for all). On a 1–4 point image quality scale in vessel delineation, our technique scored 3.8±0.4 at 4X, 2.8±0.4 at 8X and 2.3±0.6 at 12X acceleration. Using our CS sequence at 12X acceleration, we were able to acquire dynamic CE-MRA with higher spatial and temporal resolution than current clinical TWIST protocol while maintaining comparable image quality (2.8±0.5 vs. 3.0±0.4, p=NS). Conclusion Our technique is promising for dynamic CE-MRA. PMID:23801456

SU-G-IeP1-13: Sub-Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, B; Gao, H

Purpose: Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub-Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k-t space for accelerated dynamic MRI. This work is to investigate sub-Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM). Methods: The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub-Nyquist reconstruction. In PRISM, the low-rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify themore » residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k-t space is made more incoherent by sampling a different set of k-space points at different temporal frames. Results: Reconstruction results from L1-sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI. Conclusion: A sub- Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1-sparsity method.« less

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

Off-axis phase-only holograms of 3D objects using accelerated point-based Fresnel diffraction algorithm

NASA Astrophysics Data System (ADS)

Zeng, Zhenxiang; Zheng, Huadong; Yu, Yingjie; Asundi, Anand K.

2017-06-01

A method for calculating off-axis phase-only holograms of three-dimensional (3D) object using accelerated point-based Fresnel diffraction algorithm (PB-FDA) is proposed. The complex amplitude of the object points on the z-axis in hologram plane is calculated using Fresnel diffraction formula, called principal complex amplitudes (PCAs). The complex amplitudes of those off-axis object points of the same depth can be obtained by 2D shifting of PCAs. In order to improve the calculating speed of the PB-FDA, the convolution operation based on fast Fourier transform (FFT) is used to calculate the holograms rather than using the point-by-point spatial 2D shifting of the PCAs. The shortest recording distance of the PB-FDA is analyzed in order to remove the influence of multiple-order images in reconstructed images. The optimal recording distance of the PB-FDA is also analyzed to improve the quality of reconstructed images. Numerical reconstructions and optical reconstructions with a phase-only spatial light modulator (SLM) show that holographic 3D display is feasible with the proposed algorithm. The proposed PB-FDA can also avoid the influence of the zero-order image introduced by SLM in optical reconstructed images.

Real-time colour hologram generation based on ray-sampling plane with multi-GPU acceleration.

PubMed

Sato, Hirochika; Kakue, Takashi; Ichihashi, Yasuyuki; Endo, Yutaka; Wakunami, Koki; Oi, Ryutaro; Yamamoto, Kenji; Nakayama, Hirotaka; Shimobaba, Tomoyoshi; Ito, Tomoyoshi

2018-01-24

Although electro-holography can reconstruct three-dimensional (3D) motion pictures, its computational cost is too heavy to allow for real-time reconstruction of 3D motion pictures. This study explores accelerating colour hologram generation using light-ray information on a ray-sampling (RS) plane with a graphics processing unit (GPU) to realise a real-time holographic display system. We refer to an image corresponding to light-ray information as an RS image. Colour holograms were generated from three RS images with resolutions of 2,048 × 2,048; 3,072 × 3,072 and 4,096 × 4,096 pixels. The computational results indicate that the generation of the colour holograms using multiple GPUs (NVIDIA Geforce GTX 1080) was approximately 300-500 times faster than those generated using a central processing unit. In addition, the results demonstrate that 3D motion pictures were successfully reconstructed from RS images of 3,072 × 3,072 pixels at approximately 15 frames per second using an electro-holographic reconstruction system in which colour holograms were generated from RS images in real time.

Sparse Reconstruction Techniques in MRI: Methods, Applications, and Challenges to Clinical Adoption

PubMed Central

Yang, Alice Chieh-Yu; Kretzler, Madison; Sudarski, Sonja; Gulani, Vikas; Seiberlich, Nicole

2016-01-01

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in Magnetic Resonance Imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be employed to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MR imaging, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold-standards, are discussed. PMID:27003227

Regularization iteration imaging algorithm for electrical capacitance tomography

NASA Astrophysics Data System (ADS)

Tong, Guowei; Liu, Shi; Chen, Hongyan; Wang, Xueyao

2018-03-01

The image reconstruction method plays a crucial role in real-world applications of the electrical capacitance tomography technique. In this study, a new cost function that simultaneously considers the sparsity and low-rank properties of the imaging targets is proposed to improve the quality of the reconstruction images, in which the image reconstruction task is converted into an optimization problem. Within the framework of the split Bregman algorithm, an iterative scheme that splits a complicated optimization problem into several simpler sub-tasks is developed to solve the proposed cost function efficiently, in which the fast-iterative shrinkage thresholding algorithm is introduced to accelerate the convergence. Numerical experiment results verify the effectiveness of the proposed algorithm in improving the reconstruction precision and robustness.

Parallel programming of gradient-based iterative image reconstruction schemes for optical tomography.

PubMed

Hielscher, Andreas H; Bartel, Sebastian

2004-02-01

Optical tomography (OT) is a fast developing novel imaging modality that uses near-infrared (NIR) light to obtain cross-sectional views of optical properties inside the human body. A major challenge remains the time-consuming, computational-intensive image reconstruction problem that converts NIR transmission measurements into cross-sectional images. To increase the speed of iterative image reconstruction schemes that are commonly applied for OT, we have developed and implemented several parallel algorithms on a cluster of workstations. Static process distribution as well as dynamic load balancing schemes suitable for heterogeneous clusters and varying machine performances are introduced and tested. The resulting algorithms are shown to accelerate the reconstruction process to various degrees, substantially reducing the computation times for clinically relevant problems.

Multi-GPU Jacobian accelerated computing for soft-field tomography.

PubMed

Borsic, A; Attardo, E A; Halter, R J

2012-10-01

Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15-20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on four GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 min to 14 s. We regard this as an important step toward gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for EIT, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the adjoint method.

Multi-GPU Jacobian Accelerated Computing for Soft Field Tomography

PubMed Central

Borsic, A.; Attardo, E. A.; Halter, R. J.

2012-01-01

Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use Finite Element Models to represent the volume of interest and to solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are three-dimensional. Though the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in Electrical Impedance Tomography applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15 to 20 minutes with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Further, providing high-speed reconstructions are essential for some promising clinical application of EIT. For 3D problems 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In the present work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have a much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on 4 GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 minutes to 14 seconds. We regard this as an important step towards gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for Electrical Impedance Tomography, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the Adjoint Method. PMID:23010857

WE-G-18A-01: JUNIOR INVESTIGATOR WINNER - Low-Dose C-Arm Cone-Beam CT with Model-Based Image Reconstruction for High-Quality Guidance of Neurosurgical Intervention

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, A; Stayman, J; Otake, Y

Purpose: To address the challenges of image quality, radiation dose, and reconstruction speed in intraoperative cone-beam CT (CBCT) for neurosurgery by combining model-based image reconstruction (MBIR) with accelerated algorithmic and computational methods. Methods: Preclinical studies involved a mobile C-arm for CBCT imaging of two anthropomorphic head phantoms that included simulated imaging targets (ventricles, soft-tissue structures/bleeds) and neurosurgical procedures (deep brain stimulation (DBS) electrode insertion) for assessment of image quality. The penalized likelihood (PL) framework was used for MBIR, incorporating a statistical model with image regularization via an edgepreserving penalty. To accelerate PL reconstruction, the ordered-subset, separable quadratic surrogates (OS-SQS) algorithmmore » was modified to incorporate Nesterov's method and implemented on a multi-GPU system. A fair comparison of image quality between PL and conventional filtered backprojection (FBP) was performed by selecting reconstruction parameters that provided matched low-contrast spatial resolution. Results: CBCT images of the head phantoms demonstrated that PL reconstruction improved image quality (∼28% higher CNR) even at half the radiation dose (3.3 mGy) compared to FBP. A combination of Nesterov's method and fast projectors yielded a PL reconstruction run-time of 251 sec (cf., 5729 sec for OS-SQS, 13 sec for FBP). Insertion of a DBS electrode resulted in severe metal artifact streaks in FBP reconstructions, whereas PL was intrinsically robust against metal artifact. The combination of noise and artifact was reduced from 32.2 HU in FBP to 9.5 HU in PL, thereby providing better assessment of device placement and potential complications. Conclusion: The methods can be applied to intraoperative CBCT for guidance and verification of neurosurgical procedures (DBS electrode insertion, biopsy, tumor resection) and detection of complications (intracranial hemorrhage). Significant improvement in image quality, dose reduction, and reconstruction time of ∼4 min will enable practical deployment of low-dose C-arm CBCT within the operating room. AAPM Research Seed Funding (2013-2014); NIH Fellowship F32EB017571; Siemens Healthcare (XP Division)« less

A pseudo-discrete algebraic reconstruction technique (PDART) prior image-based suppression of high density artifacts in computed tomography

NASA Astrophysics Data System (ADS)

Pua, Rizza; Park, Miran; Wi, Sunhee; Cho, Seungryong

2016-12-01

We propose a hybrid metal artifact reduction (MAR) approach for computed tomography (CT) that is computationally more efficient than a fully iterative reconstruction method, but at the same time achieves superior image quality to the interpolation-based in-painting techniques. Our proposed MAR method, an image-based artifact subtraction approach, utilizes an intermediate prior image reconstructed via PDART to recover the background information underlying the high density objects. For comparison, prior images generated by total-variation minimization (TVM) algorithm, as a realization of fully iterative approach, were also utilized as intermediate images. From the simulation and real experimental results, it has been shown that PDART drastically accelerates the reconstruction to an acceptable quality of prior images. Incorporating PDART-reconstructed prior images in the proposed MAR scheme achieved higher quality images than those by a conventional in-painting method. Furthermore, the results were comparable to the fully iterative MAR that uses high-quality TVM prior images.

Harnessing AIA Diffraction Patterns to Determine Flare Footpoint Temperatures

NASA Astrophysics Data System (ADS)

Bain, H. M.; Schwartz, R. A.; Torre, G.; Krucker, S.; Raftery, C. L.

2014-12-01

In the "Standard Flare Model" energy from accelerated electrons is deposited at the footpoints of newly reconnected flare loops, heating the surrounding plasma. Understanding the relation between the multi-thermal nature of the footpoints and the energy flux from accelerated electrons is therefore fundamental to flare physics. Extreme ultraviolet (EUV) images of bright flare kernels, obtained from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory, are often saturated despite the implementation of automatic exposure control. These kernels produce diffraction patterns often seen in AIA images during the most energetic flares. We implement an automated image reconstruction procedure, which utilizes diffraction pattern artifacts, to de-saturate AIA images and reconstruct the flare brightness in saturated pixels. Applying this technique to recover the footpoint brightness in each of the AIA EUV passbands, we investigate the footpoint temperature distribution. Using observations from the Ramaty High Energy Solar Spectroscopic Imager (RHESSI), we will characterize the footpoint accelerated electron distribution of the flare. By combining these techniques, we investigate the relation between the nonthermal electron energy flux and the temperature response of the flare footpoints.

Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging.

PubMed

Wen, Qiuting; Kodiweera, Chandana; Dale, Brian M; Shivraman, Giri; Wu, Yu-Chien

2018-01-01

To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments. A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions. The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm 2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion. RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Fast sparse recovery and coherence factor weighting in optoacoustic tomography

NASA Astrophysics Data System (ADS)

He, Hailong; Prakash, Jaya; Buehler, Andreas; Ntziachristos, Vasilis

2017-03-01

Sparse recovery algorithms have shown great potential to reconstruct images with limited view datasets in optoacoustic tomography, with a disadvantage of being computational expensive. In this paper, we improve the fast convergent Split Augmented Lagrangian Shrinkage Algorithm (SALSA) method based on least square QR (LSQR) formulation for performing accelerated reconstructions. Further, coherence factor is calculated to weight the final reconstruction result, which can further reduce artifacts arising in limited-view scenarios and acoustically heterogeneous mediums. Several phantom and biological experiments indicate that the accelerated SALSA method with coherence factor (ASALSA-CF) can provide improved reconstructions and much faster convergence compared to existing sparse recovery methods.

Simultaneous 99mtc/111in spect reconstruction using accelerated convolution-based forced detection monte carlo

NASA Astrophysics Data System (ADS)

Karamat, Muhammad I.; Farncombe, Troy H.

2015-10-01

Simultaneous multi-isotope Single Photon Emission Computed Tomography (SPECT) imaging has a number of applications in cardiac, brain, and cancer imaging. The major concern however, is the significant crosstalk contamination due to photon scatter between the different isotopes. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc and 111In. We have developed an iterative image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. Our approach uses an accelerated Monte Carlo (MC) technique for the forward projection step in an iterative reconstruction algorithm. The MC estimated scatter contamination of a radionuclide contained in a given projection view is then used to compensate for the photon contamination in the acquisition window of other nuclide. We use a modified ordered subset-expectation maximization (OS-EM) algorithm named simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique was also evaluated by reconstruction of experimentally acquired phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of contrast recovery and uniformity of object background compared to alternative reconstruction methods implementing alternative scatter correction schemes (i.e., triple energy window or separately acquired projection data). In this study the evaluation is based on the quality of reconstructed images and activity estimated using Sim-OSEM. In order to quantitate the possible improvement in spatial resolution and signal to noise ratio (SNR) observed in this study, further simulation and experimental studies are required.

Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA.

PubMed

Jiansen Li; Jianqi Sun; Ying Song; Yanran Xu; Jun Zhao

2014-01-01

An effective way to improve the data acquisition speed of magnetic resonance imaging (MRI) is using under-sampled k-space data, and dictionary learning method can be used to maintain the reconstruction quality. Three-dimensional dictionary trains the atoms in dictionary in the form of blocks, which can utilize the spatial correlation among slices. Dual-dictionary learning method includes a low-resolution dictionary and a high-resolution dictionary, for sparse coding and image updating respectively. However, the amount of data is huge for three-dimensional reconstruction, especially when the number of slices is large. Thus, the procedure is time-consuming. In this paper, we first utilize the NVIDIA Corporation's compute unified device architecture (CUDA) programming model to design the parallel algorithms on graphics processing unit (GPU) to accelerate the reconstruction procedure. The main optimizations operate in the dictionary learning algorithm and the image updating part, such as the orthogonal matching pursuit (OMP) algorithm and the k-singular value decomposition (K-SVD) algorithm. Then we develop another version of CUDA code with algorithmic optimization. Experimental results show that more than 324 times of speedup is achieved compared with the CPU-only codes when the number of MRI slices is 24.

Algorithm-enabled exploration of image-quality potential of cone-beam CT in image-guided radiation therapy

NASA Astrophysics Data System (ADS)

Han, Xiao; Pearson, Erik; Pelizzari, Charles; Al-Hallaq, Hania; Sidky, Emil Y.; Bian, Junguo; Pan, Xiaochuan

2015-06-01

Kilo-voltage (KV) cone-beam computed tomography (CBCT) unit mounted onto a linear accelerator treatment system, often referred to as on-board imager (OBI), plays an increasingly important role in image-guided radiation therapy. While the FDK algorithm is currently used for reconstructing images from clinical OBI data, optimization-based reconstruction has also been investigated for OBI CBCT. An optimization-based reconstruction involves numerous parameters, which can significantly impact reconstruction properties (or utility). The success of an optimization-based reconstruction for a particular class of practical applications thus relies strongly on appropriate selection of parameter values. In the work, we focus on tailoring the constrained-TV-minimization-based reconstruction, an optimization-based reconstruction previously shown of some potential for CBCT imaging conditions of practical interest, to OBI imaging through appropriate selection of parameter values. In particular, for given real data of phantoms and patient collected with OBI CBCT, we first devise utility metrics specific to OBI-quality-assurance tasks and then apply them to guiding the selection of parameter values in constrained-TV-minimization-based reconstruction. The study results show that the reconstructions are with improvement, relative to clinical FDK reconstruction, in both visualization and quantitative assessments in terms of the devised utility metrics.

Accelerating EPI distortion correction by utilizing a modern GPU-based parallel computation.

PubMed

Yang, Yao-Hao; Huang, Teng-Yi; Wang, Fu-Nien; Chuang, Tzu-Chao; Chen, Nan-Kuei

2013-04-01

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice. Copyright © 2011 by the American Society of Neuroimaging.

In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla.

PubMed

Li, Mingyan; Jin, Jin; Zuo, Zhentao; Liu, Feng; Trakic, Adnan; Weber, Ewald; Zhuo, Yan; Xue, Rong; Crozier, Stuart

2015-03-01

Using a new rotating SENSitivity Encoding (rotating-SENSE) algorithm, we have successfully demonstrated that the rotating radiofrequency coil array (RRFCA) was capable of achieving a significant reduction in scan time and a uniform image reconstruction for a homogeneous phantom at 7 Tesla. However, at 7 Tesla the in vivo sensitivity profiles (B1(-)) become distinct at various angular positions. Therefore, sensitivity maps at other angular positions cannot be obtained by numerically rotating the acquired ones. In this work, a novel sensitivity estimation method for the RRFCA was developed and validated with human brain imaging. This method employed a library database and registration techniques to estimate coil sensitivity at an arbitrary angular position. The estimated sensitivity maps were then compared to the acquired sensitivity maps. The results indicate that the proposed method is capable of accurately estimating both magnitude and phase of sensitivity at an arbitrary angular position, which enables us to employ the rotating-SENSE algorithm to accelerate acquisition and reconstruct image. Compared to a stationary coil array with the same number of coil elements, the RRFCA was able to reconstruct images with better quality at a high reduction factor. It is hoped that the proposed rotation-dependent sensitivity estimation algorithm and the acceleration ability of the RRFCA will be particularly useful for ultra high field MRI. Copyright © 2014 Elsevier Inc. All rights reserved.

In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla

NASA Astrophysics Data System (ADS)

Li, Mingyan; Jin, Jin; Zuo, Zhentao; Liu, Feng; Trakic, Adnan; Weber, Ewald; Zhuo, Yan; Xue, Rong; Crozier, Stuart

2015-03-01

Using a new rotating SENSitivity Encoding (rotating-SENSE) algorithm, we have successfully demonstrated that the rotating radiofrequency coil array (RRFCA) was capable of achieving a significant reduction in scan time and a uniform image reconstruction for a homogeneous phantom at 7 Tesla. However, at 7 Tesla the in vivo sensitivity profiles (B1-) become distinct at various angular positions. Therefore, sensitivity maps at other angular positions cannot be obtained by numerically rotating the acquired ones. In this work, a novel sensitivity estimation method for the RRFCA was developed and validated with human brain imaging. This method employed a library database and registration techniques to estimate coil sensitivity at an arbitrary angular position. The estimated sensitivity maps were then compared to the acquired sensitivity maps. The results indicate that the proposed method is capable of accurately estimating both magnitude and phase of sensitivity at an arbitrary angular position, which enables us to employ the rotating-SENSE algorithm to accelerate acquisition and reconstruct image. Compared to a stationary coil array with the same number of coil elements, the RRFCA was able to reconstruct images with better quality at a high reduction factor. It is hoped that the proposed rotation-dependent sensitivity estimation algorithm and the acceleration ability of the RRFCA will be particularly useful for ultra high field MRI.

ACCELERATING MR PARAMETER MAPPING USING SPARSITY-PROMOTING REGULARIZATION IN PARAMETRIC DIMENSION

PubMed Central

Velikina, Julia V.; Alexander, Andrew L.; Samsonov, Alexey

2013-01-01

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which utilizes smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist. PMID:23213053

Localized Spatio-Temporal Constraints for Accelerated CMR Perfusion

PubMed Central

Akçakaya, Mehmet; Basha, Tamer A.; Pflugi, Silvio; Foppa, Murilo; Kissinger, Kraig V.; Hauser, Thomas H.; Nezafat, Reza

2013-01-01

Purpose To develop and evaluate an image reconstruction technique for cardiac MRI (CMR)perfusion that utilizes localized spatio-temporal constraints. Methods CMR perfusion plays an important role in detecting myocardial ischemia in patients with coronary artery disease. Breath-hold k-t based image acceleration techniques are typically used in CMR perfusion for superior spatial/temporal resolution, and improved coverage. In this study, we propose a novel compressed sensing based image reconstruction technique for CMR perfusion, with applicability to free-breathing examinations. This technique uses local spatio-temporal constraints by regularizing image patches across a small number of dynamics. The technique is compared to conventional dynamic-by-dynamic reconstruction, and sparsity regularization using a temporal principal-component (pc) basis, as well as zerofilled data in multi-slice 2D and 3D CMR perfusion. Qualitative image scores are used (1=poor, 4=excellent) to evaluate the technique in 3D perfusion in 10 patients and 5 healthy subjects. On 4 healthy subjects, the proposed technique was also compared to a breath-hold multi-slice 2D acquisition with parallel imaging in terms of signal intensity curves. Results The proposed technique results in images that are superior in terms of spatial and temporal blurring compared to the other techniques, even in free-breathing datasets. The image scores indicate a significant improvement compared to other techniques in 3D perfusion (2.8±0.5 vs. 2.3±0.5 for x-pc regularization, 1.7±0.5 for dynamic-by-dynamic, 1.1±0.2 for zerofilled). Signal intensity curves indicate similar dynamics of uptake between the proposed method with a 3D acquisition and the breath-hold multi-slice 2D acquisition with parallel imaging. Conclusion The proposed reconstruction utilizes sparsity regularization based on localized information in both spatial and temporal domains for highly-accelerated CMR perfusion with potential utility in free-breathing 3D acquisitions. PMID:24123058

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Accelerated gradient methods for the x-ray imaging of solar flares

NASA Astrophysics Data System (ADS)

Bonettini, S.; Prato, M.

2014-05-01

In this paper we present new optimization strategies for the reconstruction of x-ray images of solar flares by means of the data collected by the Reuven Ramaty high energy solar spectroscopic imager. The imaging concept of the satellite is based on rotating modulation collimator instruments, which allow the use of both Fourier imaging approaches and reconstruction techniques based on the straightforward inversion of the modulated count profiles. Although in the last decade, greater attention has been devoted to the former strategies due to their very limited computational cost, here we consider the latter model and investigate the effectiveness of different accelerated gradient methods for the solution of the corresponding constrained minimization problem. Moreover, regularization is introduced through either an early stopping of the iterative procedure, or a Tikhonov term added to the discrepancy function by means of a discrepancy principle accounting for the Poisson nature of the noise affecting the data.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Accelerated self-gated UTE MRI of the murine heart

NASA Astrophysics Data System (ADS)

Motaal, Abdallah G.; Noorman, Nils; De Graaf, Wolter L.; Florack, Luc J.; Nicolay, Klaas; Strijkers, Gustav J.

2014-03-01

We introduce a new protocol to obtain radial Ultra-Short TE (UTE) MRI Cine of the beating mouse heart within reasonable measurement time. The method is based on a self-gated UTE with golden angle radial acquisition and compressed sensing reconstruction. The stochastic nature of the retrospective triggering acquisition scheme produces an under-sampled and random kt-space filling that allows for compressed sensing reconstruction, hence reducing scan time. As a standard, an intragate multislice FLASH sequence with an acquisition time of 4.5 min per slice was used to produce standard Cine movies of 4 mice hearts with 15 frames per cardiac cycle. The proposed self-gated sequence is used to produce Cine movies with short echo time. The total scan time was 11 min per slice. 6 slices were planned to cover the heart from the base to the apex. 2X, 4X and 6X under-sampled k-spaces cine movies were produced from 2, 1 and 0.7 min data acquisitions for each slice. The accelerated cine movies of the mouse hearts were successfully reconstructed with a compressed sensing algorithm. Compared to the FLASH cine images, the UTE images showed much less flow artifacts due to the short echo time. Besides, the accelerated movies had high image quality and the undersampling artifacts were effectively removed. Left ventricular functional parameters derived from the standard and the accelerated cine movies were nearly identical.

GPU-accelerated regularized iterative reconstruction for few-view cone beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca; Després, Philippe, E-mail: philippe.despres@phy.ulaval.ca

2015-04-15

Purpose: The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. Methods: The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it ismore » implemented on a graphics processing unit, using parallelization to accelerate computations. Results: The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1–2 min and are compatible with the typical clinical workflow for nonreal-time applications. Conclusions: Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.« less

Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

NASA Astrophysics Data System (ADS)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Inter-slice Leakage Artifact Reduction Technique for Simultaneous Multi-Slice Acquisitions

PubMed Central

Cauley, Stephen F.; Polimeni, Jonathan R.; Bhat, Himanshu; Wang, Dingxin; Wald, Lawrence L.; Setsompop, Kawin

2015-01-01

Purpose Controlled aliasing techniques for simultaneously acquired EPI slices have been shown to significantly increase the temporal efficiency for both diffusion-weighted imaging (DWI) and fMRI studies. The “slice-GRAPPA” (SG) method has been widely used to reconstruct such data. We investigate robust optimization techniques for SG to ensure image reconstruction accuracy through a reduction of leakage artifacts. Methods Split slice-GRAPPA (SP-SG) is proposed as an alternative kernel optimization method. The performance of SP-SG is compared to standard SG using data collected on a spherical phantom and in-vivo on two subjects at 3T. Slice accelerated and non-accelerated data were collected for a spin-echo diffusion weighted acquisition. Signal leakage metrics and time-series SNR were used to quantify the performance of the kernel fitting approaches. Results The SP-SG optimization strategy significantly reduces leakage artifacts for both phantom and in-vivo acquisitions. In addition, a significant boost in time-series SNR for in-vivo diffusion weighted acquisitions with in-plane 2× and slice 3× accelerations was observed with the SP-SG approach. Conclusion By minimizing the influence of leakage artifacts during the training of slice-GRAPPA kernels, we have significantly improved reconstruction accuracy. Our robust kernel fitting strategy should enable better reconstruction accuracy and higher slice-acceleration across many applications. PMID:23963964

Calibrationless parallel magnetic resonance imaging: a joint sparsity model.

PubMed

Majumdar, Angshul; Chaudhury, Kunal Narayan; Ward, Rabab

2013-12-05

State-of-the-art parallel MRI techniques either explicitly or implicitly require certain parameters to be estimated, e.g., the sensitivity map for SENSE, SMASH and interpolation weights for GRAPPA, SPIRiT. Thus all these techniques are sensitive to the calibration (parameter estimation) stage. In this work, we have proposed a parallel MRI technique that does not require any calibration but yields reconstruction results that are at par with (or even better than) state-of-the-art methods in parallel MRI. Our proposed method required solving non-convex analysis and synthesis prior joint-sparsity problems. This work also derives the algorithms for solving them. Experimental validation was carried out on two datasets-eight channel brain and eight channel Shepp-Logan phantom. Two sampling methods were used-Variable Density Random sampling and non-Cartesian Radial sampling. For the brain data, acceleration factor of 4 was used and for the other an acceleration factor of 6 was used. The reconstruction results were quantitatively evaluated based on the Normalised Mean Squared Error between the reconstructed image and the originals. The qualitative evaluation was based on the actual reconstructed images. We compared our work with four state-of-the-art parallel imaging techniques; two calibrated methods-CS SENSE and l1SPIRiT and two calibration free techniques-Distributed CS and SAKE. Our method yields better reconstruction results than all of them.

Using a local low rank plus sparse reconstruction to accelerate dynamic hyperpolarized 13C imaging using the bSSFP sequence

NASA Astrophysics Data System (ADS)

Milshteyn, Eugene; von Morze, Cornelius; Reed, Galen D.; Shang, Hong; Shin, Peter J.; Larson, Peder E. Z.; Vigneron, Daniel B.

2018-05-01

Acceleration of dynamic 2D (T2 Mapping) and 3D hyperpolarized 13C MRI acquisitions using the balanced steady-state free precession sequence was achieved with a specialized reconstruction method, based on the combination of low rank plus sparse and local low rank reconstructions. Methods were validated using both retrospectively and prospectively undersampled in vivo data from normal rats and tumor-bearing mice. Four-fold acceleration of 1-2 mm isotropic 3D dynamic acquisitions with 2-5 s temporal resolution and two-fold acceleration of 0.25-1 mm2 2D dynamic acquisitions was achieved. This enabled visualization of the biodistribution of [2-13C]pyruvate, [1-13C]lactate, [13C, 15N2]urea, and HP001 within heart, kidneys, vasculature, and tumor, as well as calculation of high resolution T2 maps.

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging.

PubMed

Wen, Tiexiang; Li, Ling; Zhu, Qingsong; Qin, Wenjian; Gu, Jia; Yang, Feng; Xie, Yaoqin

2017-07-01

Volume reconstruction method plays an important role in improving reconstructed volumetric image quality for freehand three-dimensional (3D) ultrasound imaging. By utilizing the capability of programmable graphics processing unit (GPU), we can achieve a real-time incremental volume reconstruction at a speed of 25-50 frames per second (fps). After incremental reconstruction and visualization, hole-filling is performed on GPU to fill remaining empty voxels. However, traditional pixel nearest neighbor-based hole-filling fails to reconstruct volume with high image quality. On the contrary, the kernel regression provides an accurate volume reconstruction method for 3D ultrasound imaging but with the cost of heavy computational complexity. In this paper, a GPU-based fast kernel regression method is proposed for high-quality volume after the incremental reconstruction of freehand ultrasound. The experimental results show that improved image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of [Formula: see text] and kernel bandwidth of 1.0. The computational performance of the proposed GPU-based method can be over 200 times faster than that on central processing unit (CPU), and the volume with size of 50 million voxels in our experiment can be reconstructed within 10 seconds.

Fast higher-order MR image reconstruction using singular-vector separation.

PubMed

Wilm, Bertram J; Barmet, Christoph; Pruessmann, Klaas P

2012-07-01

Medical resonance imaging (MRI) conventionally relies on spatially linear gradient fields for image encoding. However, in practice various sources of nonlinear fields can perturb the encoding process and give rise to artifacts unless they are suitably addressed at the reconstruction level. Accounting for field perturbations that are neither linear in space nor constant over time, i.e., dynamic higher-order fields, is particularly challenging. It was previously shown to be feasible with conjugate-gradient iteration. However, so far this approach has been relatively slow due to the need to carry out explicit matrix-vector multiplications in each cycle. In this work, it is proposed to accelerate higher-order reconstruction by expanding the encoding matrix such that fast Fourier transform can be employed for more efficient matrix-vector computation. The underlying principle is to represent the perturbing terms as sums of separable functions of space and time. Compact representations with this property are found by singular-vector analysis of the perturbing matrix. Guidelines for balancing the accuracy and speed of the resulting algorithm are derived by error propagation analysis. The proposed technique is demonstrated for the case of higher-order field perturbations due to eddy currents caused by diffusion weighting. In this example, image reconstruction was accelerated by two orders of magnitude.

Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study.

PubMed

Wang, Chunhao; Yin, Fang-Fang; Kirkpatrick, John P; Chang, Zheng

2017-08-01

To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant K trans in the extended Tofts model and blood flow F B and blood volume V B from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.

Autocalibrating motion-corrected wave-encoding for highly accelerated free-breathing abdominal MRI.

PubMed

Chen, Feiyu; Zhang, Tao; Cheng, Joseph Y; Shi, Xinwei; Pauly, John M; Vasanawala, Shreyas S

2017-11-01

To develop a motion-robust wave-encoding technique for highly accelerated free-breathing abdominal MRI. A comprehensive 3D wave-encoding-based method was developed to enable fast free-breathing abdominal imaging: (a) auto-calibration for wave-encoding was designed to avoid extra scan for coil sensitivity measurement; (b) intrinsic butterfly navigators were used to track respiratory motion; (c) variable-density sampling was included to enable compressed sensing; (d) golden-angle radial-Cartesian hybrid view-ordering was incorporated to improve motion robustness; and (e) localized rigid motion correction was combined with parallel imaging compressed sensing reconstruction to reconstruct the highly accelerated wave-encoded datasets. The proposed method was tested on six subjects and image quality was compared with standard accelerated Cartesian acquisition both with and without respiratory triggering. Inverse gradient entropy and normalized gradient squared metrics were calculated, testing whether image quality was improved using paired t-tests. For respiratory-triggered scans, wave-encoding significantly reduced residual aliasing and blurring compared with standard Cartesian acquisition (metrics suggesting P < 0.05). For non-respiratory-triggered scans, the proposed method yielded significantly better motion correction compared with standard motion-corrected Cartesian acquisition (metrics suggesting P < 0.01). The proposed methods can reduce motion artifacts and improve overall image quality of highly accelerated free-breathing abdominal MRI. Magn Reson Med 78:1757-1766, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Dual-TRACER: High resolution fMRI with constrained evolution reconstruction.

PubMed

Li, Xuesong; Ma, Xiaodong; Li, Lyu; Zhang, Zhe; Zhang, Xue; Tong, Yan; Wang, Lihong; Sen Song; Guo, Hua

2018-01-01

fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm 2 ) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection. Copyright © 2017 Elsevier Inc. All rights reserved.

An iterative reduced field-of-view reconstruction for periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI.

PubMed

Lin, Jyh-Miin; Patterson, Andrew J; Chang, Hing-Chiu; Gillard, Jonathan H; Graves, Martin J

2015-10-01

To propose a new reduced field-of-view (rFOV) strategy for iterative reconstructions in a clinical environment. Iterative reconstructions can incorporate regularization terms to improve the image quality of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI. However, the large amount of calculations required for full FOV iterative reconstructions has posed a huge computational challenge for clinical usage. By subdividing the entire problem into smaller rFOVs, the iterative reconstruction can be accelerated on a desktop with a single graphic processing unit (GPU). This rFOV strategy divides the iterative reconstruction into blocks, based on the block-diagonal dominant structure. A near real-time reconstruction system was developed for the clinical MR unit, and parallel computing was implemented using the object-oriented model. In addition, the Toeplitz method was implemented on the GPU to reduce the time required for full interpolation. Using the data acquired from the PROPELLER MRI, the reconstructed images were then saved in the digital imaging and communications in medicine format. The proposed rFOV reconstruction reduced the gridding time by 97%, as the total iteration time was 3 s even with multiple processes running. A phantom study showed that the structure similarity index for rFOV reconstruction was statistically superior to conventional density compensation (p < 0.001). In vivo study validated the increased signal-to-noise ratio, which is over four times higher than with density compensation. Image sharpness index was improved using the regularized reconstruction implemented. The rFOV strategy permits near real-time iterative reconstruction to improve the image quality of PROPELLER images. Substantial improvements in image quality metrics were validated in the experiments. The concept of rFOV reconstruction may potentially be applied to other kinds of iterative reconstructions for shortened reconstruction duration.

Acceleration of fluoro-CT reconstruction for a mobile C-Arm on GPU and FPGA hardware: a simulation study

NASA Astrophysics Data System (ADS)

Xue, Xinwei; Cheryauka, Arvi; Tubbs, David

2006-03-01

CT imaging in interventional and minimally-invasive surgery requires high-performance computing solutions that meet operational room demands, healthcare business requirements, and the constraints of a mobile C-arm system. The computational requirements of clinical procedures using CT-like data are increasing rapidly, mainly due to the need for rapid access to medical imagery during critical surgical procedures. The highly parallel nature of Radon transform and CT algorithms enables embedded computing solutions utilizing a parallel processing architecture to realize a significant gain of computational intensity with comparable hardware and program coding/testing expenses. In this paper, using a sample 2D and 3D CT problem, we explore the programming challenges and the potential benefits of embedded computing using commodity hardware components. The accuracy and performance results obtained on three computational platforms: a single CPU, a single GPU, and a solution based on FPGA technology have been analyzed. We have shown that hardware-accelerated CT image reconstruction can be achieved with similar levels of noise and clarity of feature when compared to program execution on a CPU, but gaining a performance increase at one or more orders of magnitude faster. 3D cone-beam or helical CT reconstruction and a variety of volumetric image processing applications will benefit from similar accelerations.

Multicontrast reconstruction using compressed sensing with low rank and spatially varying edge-preserving constraints for high-resolution MR characterization of myocardial infarction.

PubMed

Zhang, Li; Athavale, Prashant; Pop, Mihaela; Wright, Graham A

2017-08-01

To enable robust reconstruction for highly accelerated three-dimensional multicontrast late enhancement imaging to provide improved MR characterization of myocardial infarction with isotropic high spatial resolution. A new method using compressed sensing with low rank and spatially varying edge-preserving constraints (CS-LASER) is proposed to improve the reconstruction of fine image details from highly undersampled data. CS-LASER leverages the low rank feature of the multicontrast volume series in MR relaxation and integrates spatially varying edge preservation into the explicit low rank constrained compressed sensing framework using weighted total variation. With an orthogonal temporal basis pre-estimated, a multiscale iterative reconstruction framework is proposed to enable the practice of CS-LASER with spatially varying weights of appropriate accuracy. In in vivo pig studies with both retrospective and prospective undersamplings, CS-LASER preserved fine image details better and presented tissue characteristics with a higher degree of consistency with histopathology, particularly in the peri-infarct region, than an alternative technique for different acceleration rates. An isotropic resolution of 1.5 mm was achieved in vivo within a single breath-hold using the proposed techniques. Accelerated three-dimensional multicontrast late enhancement with CS-LASER can achieve improved MR characterization of myocardial infarction with high spatial resolution. Magn Reson Med 78:598-610, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

K-space reconstruction with anisotropic kernel support (KARAOKE) for ultrafast partially parallel imaging.

PubMed

Miao, Jun; Wong, Wilbur C K; Narayan, Sreenath; Wilson, David L

2011-11-01

Partially parallel imaging (PPI) greatly accelerates MR imaging by using surface coil arrays and under-sampling k-space. However, the reduction factor (R) in PPI is theoretically constrained by the number of coils (N(C)). A symmetrically shaped kernel is typically used, but this often prevents even the theoretically possible R from being achieved. Here, the authors propose a kernel design method to accelerate PPI faster than R = N(C). K-space data demonstrates an anisotropic pattern that is correlated with the object itself and to the asymmetry of the coil sensitivity profile, which is caused by coil placement and B(1) inhomogeneity. From spatial analysis theory, reconstruction of such pattern is best achieved by a signal-dependent anisotropic shape kernel. As a result, the authors propose the use of asymmetric kernels to improve k-space reconstruction. The authors fit a bivariate Gaussian function to the local signal magnitude of each coil, then threshold this function to extract the kernel elements. A perceptual difference model (Case-PDM) was employed to quantitatively evaluate image quality. A MR phantom experiment showed that k-space anisotropy increased as a function of magnetic field strength. The authors tested a K-spAce Reconstruction with AnisOtropic KErnel support ("KARAOKE") algorithm with both MR phantom and in vivo data sets, and compared the reconstructions to those produced by GRAPPA, a popular PPI reconstruction method. By exploiting k-space anisotropy, KARAOKE was able to better preserve edges, which is particularly useful for cardiac imaging and motion correction, while GRAPPA failed at a high R near or exceeding N(C). KARAOKE performed comparably to GRAPPA at low Rs. As a rule of thumb, KARAOKE reconstruction should always be used for higher quality k-space reconstruction, particularly when PPI data is acquired at high Rs and/or high field strength.

K-space reconstruction with anisotropic kernel support (KARAOKE) for ultrafast partially parallel imaging

PubMed Central

Miao, Jun; Wong, Wilbur C. K.; Narayan, Sreenath; Wilson, David L.

2011-01-01

Purpose: Partially parallel imaging (PPI) greatly accelerates MR imaging by using surface coil arrays and under-sampling k-space. However, the reduction factor (R) in PPI is theoretically constrained by the number of coils (NC). A symmetrically shaped kernel is typically used, but this often prevents even the theoretically possible R from being achieved. Here, the authors propose a kernel design method to accelerate PPI faster than R = NC. Methods: K-space data demonstrates an anisotropic pattern that is correlated with the object itself and to the asymmetry of the coil sensitivity profile, which is caused by coil placement and B1 inhomogeneity. From spatial analysis theory, reconstruction of such pattern is best achieved by a signal-dependent anisotropic shape kernel. As a result, the authors propose the use of asymmetric kernels to improve k-space reconstruction. The authors fit a bivariate Gaussian function to the local signal magnitude of each coil, then threshold this function to extract the kernel elements. A perceptual difference model (Case-PDM) was employed to quantitatively evaluate image quality. Results: A MR phantom experiment showed that k-space anisotropy increased as a function of magnetic field strength. The authors tested a K-spAce Reconstruction with AnisOtropic KErnel support (“KARAOKE”) algorithm with both MR phantom and in vivo data sets, and compared the reconstructions to those produced by GRAPPA, a popular PPI reconstruction method. By exploiting k-space anisotropy, KARAOKE was able to better preserve edges, which is particularly useful for cardiac imaging and motion correction, while GRAPPA failed at a high R near or exceeding NC. KARAOKE performed comparably to GRAPPA at low Rs. Conclusions: As a rule of thumb, KARAOKE reconstruction should always be used for higher quality k-space reconstruction, particularly when PPI data is acquired at high Rs and∕or high field strength. PMID:22047378

Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods

PubMed Central

Smith, David S.; Gore, John C.; Yankeelov, Thomas E.; Welch, E. Brian

2012-01-01

Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 40962 or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 10242 and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images. PMID:22481908

Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods.

PubMed

Smith, David S; Gore, John C; Yankeelov, Thomas E; Welch, E Brian

2012-01-01

Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 4096(2) or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 1024(2) and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images.

Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI.

PubMed

Olafsson, Valur T; Noll, Douglas C; Fessler, Jeffrey A

2018-02-01

Penalized least-squares iterative image reconstruction algorithms used for spatial resolution-limited imaging, such as functional magnetic resonance imaging (fMRI), commonly use a quadratic roughness penalty to regularize the reconstructed images. When used for complex-valued images, the conventional roughness penalty regularizes the real and imaginary parts equally. However, these imaging methods sometimes benefit from separate penalties for each part. The spatial smoothness from the roughness penalty on the reconstructed image is dictated by the regularization parameter(s). One method to set the parameter to a desired smoothness level is to evaluate the full width at half maximum of the reconstruction method's local impulse response. Previous work has shown that when using the conventional quadratic roughness penalty, one can approximate the local impulse response using an FFT-based calculation. However, that acceleration method cannot be applied directly for separate real and imaginary regularization. This paper proposes a fast and stable calculation for this case that also uses FFT-based calculations to approximate the local impulse responses of the real and imaginary parts. This approach is demonstrated with a quadratic image reconstruction of fMRI data that uses separate roughness penalties for the real and imaginary parts.

WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Y; Mutic, S; Du, D

Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported intomore » the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green receive travel reimbursement from ViewRay. S. Mutic has consulting and research agreements with ViewRay. Q. Zeng, R. Nana, J.L. Patrick, S. Shvartsman and J.F. Dempsey are ViewRay employees.« less

High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware.

PubMed

Freiberger, Manuel; Egger, Herbert; Liebmann, Manfred; Scharfetter, Hermann

2011-11-01

Image reconstruction in fluorescence optical tomography is a three-dimensional nonlinear ill-posed problem governed by a system of partial differential equations. In this paper we demonstrate that a combination of state of the art numerical algorithms and a careful hardware optimized implementation allows to solve this large-scale inverse problem in a few seconds on standard desktop PCs with modern graphics hardware. In particular, we present methods to solve not only the forward but also the non-linear inverse problem by massively parallel programming on graphics processors. A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images.

Laser-wakefield accelerators as hard x-ray sources for 3D medical imaging of human bone

PubMed Central

Cole, J. M.; Wood, J. C.; Lopes, N. C.; Poder, K.; Abel, R. L.; Alatabi, S.; Bryant, J. S. J.; Jin, A.; Kneip, S.; Mecseki, K.; Symes, D. R.; Mangles, S. P. D.; Najmudin, Z.

2015-01-01

A bright μm-sized source of hard synchrotron x-rays (critical energy Ecrit > 30 keV) based on the betatron oscillations of laser wakefield accelerated electrons has been developed. The potential of this source for medical imaging was demonstrated by performing micro-computed tomography of a human femoral trabecular bone sample, allowing full 3D reconstruction to a resolution below 50 μm. The use of a 1 cm long wakefield accelerator means that the length of the beamline (excluding the laser) is dominated by the x-ray imaging distances rather than the electron acceleration distances. The source possesses high peak brightness, which allows each image to be recorded with a single exposure and reduces the time required for a full tomographic scan. These properties make this an interesting laboratory source for many tomographic imaging applications. PMID:26283308

Accelerated gradient based diffuse optical tomographic image reconstruction.

PubMed

Biswas, Samir Kumar; Rajan, K; Vasu, R M

2011-01-01

Fast reconstruction of interior optical parameter distribution using a new approach called Broyden-based model iterative image reconstruction (BMOBIIR) and adjoint Broyden-based MOBIIR (ABMOBIIR) of a tissue and a tissue mimicking phantom from boundary measurement data in diffuse optical tomography (DOT). DOT is a nonlinear and ill-posed inverse problem. Newton-based MOBIIR algorithm, which is generally used, requires repeated evaluation of the Jacobian which consumes bulk of the computation time for reconstruction. In this study, we propose a Broyden approach-based accelerated scheme for Jacobian computation and it is combined with conjugate gradient scheme (CGS) for fast reconstruction. The method makes explicit use of secant and adjoint information that can be obtained from forward solution of the diffusion equation. This approach reduces the computational time many fold by approximating the system Jacobian successively through low-rank updates. Simulation studies have been carried out with single as well as multiple inhomogeneities. Algorithms are validated using an experimental study carried out on a pork tissue with fat acting as an inhomogeneity. The results obtained through the proposed BMOBIIR and ABMOBIIR approaches are compared with those of Newton-based MOBIIR algorithm. The mean squared error and execution time are used as metrics for comparing the results of reconstruction. We have shown through experimental and simulation studies that Broyden-based MOBIIR and adjoint Broyden-based methods are capable of reconstructing single as well as multiple inhomogeneities in tissue and a tissue-mimicking phantom. Broyden MOBIIR and adjoint Broyden MOBIIR methods are computationally simple and they result in much faster implementations because they avoid direct evaluation of Jacobian. The image reconstructions have been carried out with different initial values using Newton, Broyden, and adjoint Broyden approaches. These algorithms work well when the initial guess is close to the true solution. However, when initial guess is far away from true solution, Newton-based MOBIIR gives better reconstructed images. The proposed methods are found to be stable with noisy measurement data.

Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation.

PubMed

Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

2016-02-07

Time-of-flight (TOF) positron emission tomography (PET) technology has recently regained popularity in clinical PET studies for improving image quality and lesion detectability. Using TOF information, the spatial location of annihilation events is confined to a number of image voxels along each line of response, thereby the cross-dependencies of image voxels are reduced, which in turns results in improved signal-to-noise ratio and convergence rate. In this work, we propose a novel approach to further improve the convergence of the expectation maximization (EM)-based TOF PET image reconstruction algorithm through subsetization of emission data over TOF bins as well as azimuthal bins. Given the prevalence of TOF PET, we elaborated the practical and efficient implementation of TOF PET image reconstruction through the pre-computation of TOF weighting coefficients while exploiting the same in-plane and axial symmetries used in pre-computation of geometric system matrix. In the proposed subsetization approach, TOF PET data were partitioned into a number of interleaved TOF subsets, with the aim of reducing the spatial coupling of TOF bins and therefore to improve the convergence of the standard maximum likelihood expectation maximization (MLEM) and ordered subsets EM (OSEM) algorithms. The comparison of on-the-fly and pre-computed TOF projections showed that the pre-computation of the TOF weighting coefficients can considerably reduce the computation time of TOF PET image reconstruction. The convergence rate and bias-variance performance of the proposed TOF subsetization scheme were evaluated using simulated, experimental phantom and clinical studies. Simulations demonstrated that as the number of TOF subsets is increased, the convergence rate of MLEM and OSEM algorithms is improved. It was also found that for the same computation time, the proposed subsetization gives rise to further convergence. The bias-variance analysis of the experimental NEMA phantom and a clinical FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation

NASA Astrophysics Data System (ADS)

Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

2016-02-01

Time-of-flight (TOF) positron emission tomography (PET) technology has recently regained popularity in clinical PET studies for improving image quality and lesion detectability. Using TOF information, the spatial location of annihilation events is confined to a number of image voxels along each line of response, thereby the cross-dependencies of image voxels are reduced, which in turns results in improved signal-to-noise ratio and convergence rate. In this work, we propose a novel approach to further improve the convergence of the expectation maximization (EM)-based TOF PET image reconstruction algorithm through subsetization of emission data over TOF bins as well as azimuthal bins. Given the prevalence of TOF PET, we elaborated the practical and efficient implementation of TOF PET image reconstruction through the pre-computation of TOF weighting coefficients while exploiting the same in-plane and axial symmetries used in pre-computation of geometric system matrix. In the proposed subsetization approach, TOF PET data were partitioned into a number of interleaved TOF subsets, with the aim of reducing the spatial coupling of TOF bins and therefore to improve the convergence of the standard maximum likelihood expectation maximization (MLEM) and ordered subsets EM (OSEM) algorithms. The comparison of on-the-fly and pre-computed TOF projections showed that the pre-computation of the TOF weighting coefficients can considerably reduce the computation time of TOF PET image reconstruction. The convergence rate and bias-variance performance of the proposed TOF subsetization scheme were evaluated using simulated, experimental phantom and clinical studies. Simulations demonstrated that as the number of TOF subsets is increased, the convergence rate of MLEM and OSEM algorithms is improved. It was also found that for the same computation time, the proposed subsetization gives rise to further convergence. The bias-variance analysis of the experimental NEMA phantom and a clinical FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

Reducing the number of reconstructions needed for estimating channelized observer performance

NASA Astrophysics Data System (ADS)

Pineda, Angel R.; Miedema, Hope; Brenner, Melissa; Altaf, Sana

2018-03-01

A challenge for task-based optimization is the time required for each reconstructed image in applications where reconstructions are time consuming. Our goal is to reduce the number of reconstructions needed to estimate the area under the receiver operating characteristic curve (AUC) of the infinitely-trained optimal channelized linear observer. We explore the use of classifiers which either do not invert the channel covariance matrix or do feature selection. We also study the assumption that multiple low contrast signals in the same image of a non-linear reconstruction do not significantly change the estimate of the AUC. We compared the AUC of several classifiers (Hotelling, logistic regression, logistic regression using Firth bias reduction and the least absolute shrinkage and selection operator (LASSO)) with a small number of observations both for normal simulated data and images from a total variation reconstruction in magnetic resonance imaging (MRI). We used 10 Laguerre-Gauss channels and the Mann-Whitney estimator for AUC. For this data, our results show that at small sample sizes feature selection using the LASSO technique can decrease bias of the AUC estimation with increased variance and that for large sample sizes the difference between these classifiers is small. We also compared the use of multiple signals in a single reconstructed image to reduce the number of reconstructions in a total variation reconstruction for accelerated imaging in MRI. We found that AUC estimation using multiple low contrast signals in the same image resulted in similar AUC estimates as doing a single reconstruction per signal leading to a 13x reduction in the number of reconstructions needed.

Using a local low rank plus sparse reconstruction to accelerate dynamic hyperpolarized 13C imaging using the bSSFP sequence.

PubMed

Milshteyn, Eugene; von Morze, Cornelius; Reed, Galen D; Shang, Hong; Shin, Peter J; Larson, Peder E Z; Vigneron, Daniel B

2018-05-01

Acceleration of dynamic 2D (T 2 Mapping) and 3D hyperpolarized 13 C MRI acquisitions using the balanced steady-state free precession sequence was achieved with a specialized reconstruction method, based on the combination of low rank plus sparse and local low rank reconstructions. Methods were validated using both retrospectively and prospectively undersampled in vivo data from normal rats and tumor-bearing mice. Four-fold acceleration of 1-2 mm isotropic 3D dynamic acquisitions with 2-5 s temporal resolution and two-fold acceleration of 0.25-1 mm 2 2D dynamic acquisitions was achieved. This enabled visualization of the biodistribution of [2- 13 C]pyruvate, [1- 13 C]lactate, [ 13 C,  15 N 2 ]urea, and HP001 within heart, kidneys, vasculature, and tumor, as well as calculation of high resolution T 2 maps. Copyright © 2018 Elsevier Inc. All rights reserved.

A fast 4D cone beam CT reconstruction method based on the OSC-TV algorithm.

PubMed

Mascolo-Fortin, Julia; Matenine, Dmitri; Archambault, Louis; Després, Philippe

2018-01-01

Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.

An extended algebraic reconstruction technique (E-ART) for dual spectral CT.

PubMed

Zhao, Yunsong; Zhao, Xing; Zhang, Peng

2015-03-01

Compared with standard computed tomography (CT), dual spectral CT (DSCT) has many advantages for object separation, contrast enhancement, artifact reduction, and material composition assessment. But it is generally difficult to reconstruct images from polychromatic projections acquired by DSCT, because of the nonlinear relation between the polychromatic projections and the images to be reconstructed. This paper first models the DSCT reconstruction problem as a nonlinear system problem; and then extend the classic ART method to solve the nonlinear system. One feature of the proposed method is its flexibility. It fits for any scanning configurations commonly used and does not require consistent rays for different X-ray spectra. Another feature of the proposed method is its high degree of parallelism, which means that the method is suitable for acceleration on GPUs (graphic processing units) or other parallel systems. The method is validated with numerical experiments from simulated noise free and noisy data. High quality images are reconstructed with the proposed method from the polychromatic projections of DSCT. The reconstructed images are still satisfactory even if there are certain errors in the estimated X-ray spectra.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy.

PubMed

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-10-01

Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4-6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3-8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy

PubMed Central

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-01-01

Purpose: Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4–6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. Methods: The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Results: Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3–8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. Conclusions: 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts. PMID:21992381

Implementation of compressive sensing for preclinical cine-MRI

NASA Astrophysics Data System (ADS)

Tan, Elliot; Yang, Ming; Ma, Lixin; Zheng, Yahong Rosa

2014-03-01

This paper presents a practical implementation of Compressive Sensing (CS) for a preclinical MRI machine to acquire randomly undersampled k-space data in cardiac function imaging applications. First, random undersampling masks were generated based on Gaussian, Cauchy, wrapped Cauchy and von Mises probability distribution functions by the inverse transform method. The best masks for undersampling ratios of 0.3, 0.4 and 0.5 were chosen for animal experimentation, and were programmed into a Bruker Avance III BioSpec 7.0T MRI system through method programming in ParaVision. Three undersampled mouse heart datasets were obtained using a fast low angle shot (FLASH) sequence, along with a control undersampled phantom dataset. ECG and respiratory gating was used to obtain high quality images. After CS reconstructions were applied to all acquired data, resulting images were quantitatively analyzed using the performance metrics of reconstruction error and Structural Similarity Index (SSIM). The comparative analysis indicated that CS reconstructed images from MRI machine undersampled data were indeed comparable to CS reconstructed images from retrospective undersampled data, and that CS techniques are practical in a preclinical setting. The implementation achieved 2 to 4 times acceleration for image acquisition and satisfactory quality of image reconstruction.

Acceleration of integral imaging based incoherent Fourier hologram capture using graphic processing unit.

PubMed

Jeong, Kyeong-Min; Kim, Hee-Seung; Hong, Sung-In; Lee, Sung-Keun; Jo, Na-Young; Kim, Yong-Soo; Lim, Hong-Gi; Park, Jae-Hyeung

2012-10-08

Speed enhancement of integral imaging based incoherent Fourier hologram capture using a graphic processing unit is reported. Integral imaging based method enables exact hologram capture of real-existing three-dimensional objects under regular incoherent illumination. In our implementation, we apply parallel computation scheme using the graphic processing unit, accelerating the processing speed. Using enhanced speed of hologram capture, we also implement a pseudo real-time hologram capture and optical reconstruction system. The overall operation speed is measured to be 1 frame per second.

Accelerated Fractional Ventilation Imaging with Hyperpolarized Gas MRI

PubMed Central

Emami, Kiarash; Xu, Yinan; Hamedani, Hooman; Profka, Harrilla; Kadlecek, Stephen; Xin, Yi; Ishii, Masaru; Rizi, Rahim R.

2013-01-01

PURPOSE To investigate the utility of accelerated imaging to enhance multi-breath fractional ventilation (r) measurement accuracy using HP gas MRI. Undersampling shortens the breath-hold time, thereby reducing the O2-induced signal decay and allows subjects to maintain a more physiologically relevant breathing pattern. Additionally it may improve r estimation accuracy by reducing RF destruction of HP gas. METHODS Image acceleration was achieved by using an 8-channel phased array coil. Undersampled image acquisition was simulated in a series of ventilation images and images were reconstructed for various matrix sizes (48–128) using GRAPPA. Parallel accelerated r imaging was also performed on five mechanically ventilated pigs. RESULTS Optimal acceleration factor was fairly invariable (2.0–2.2×) over the range of simulated resolutions. Estimation accuracy progressively improved with higher resolutions (39–51% error reduction). In vivo r values were not significantly different between the two methods: 0.27±0.09, 0.35±0.06, 0.40±0.04 (standard) versus 0.23±0.05, 0.34±0.03, 0.37±0.02 (accelerated); for anterior, medial and posterior slices, respectively, whereas the corresponding vertical r gradients were significant (P < 0.001): 0.021±0.007 (standard) versus 0.019±0.005 (accelerated) [cm−1]. CONCLUSION Quadruple phased array coil simulations resulted in an optimal acceleration factor of ~2× independent of imaging resolution. Results advocate undersampled image acceleration to improve accuracy of fractional ventilation measurement with HP gas MRI. PMID:23400938

First-pass myocardial perfusion imaging with whole-heart coverage using L1-SPIRiT accelerated variable density spiral trajectories

PubMed Central

Yang, Yang; Kramer, Christopher M.; Shaw, Peter W.; Meyer, Craig H.; Salerno, Michael

2015-01-01

Purpose To design and evaluate 2D L1-SPIRiT accelerated spiral pulse sequences for first-pass myocardial perfusion imaging with whole heart coverage capable of measuring 8 slices at 2 mm in-plane resolution at heart rates up to 125 beats per minute (BPM). Methods Combinations of 5 different spiral trajectories and 4 k-t sampling patterns were retrospectively simulated in 25 fully sampled datasets and reconstructed with L1-SPIRiT to determine the best combination of parameters. Two candidate sequences were prospectively evaluated in 34 human subjects to assess in-vivo performance. Results A dual density broad transition spiral trajectory with either angularly uniform or golden angle in time k-t sampling pattern had the largest structural similarity (SSIM) and smallest root mean square error (RMSE) from the retrospective simulation, and the L1-SPIRiT reconstruction had well-preserved temporal dynamics. In vivo data demonstrated that both of the sampling patterns could produce high quality perfusion images with whole-heart coverage. Conclusion First-pass myocardial perfusion imaging using accelerated spirals with optimized trajectory and k-t sampling pattern can produce high quality 2D-perfusion images with wholeheart coverage at the heart rates up to 125 BPM. PMID:26538511

Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.

PubMed

Fessler, J A; Booth, S D

1999-01-01

Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.

Whole-body nonenhanced PET/MR versus PET/CT in the staging and restaging of cancers: preliminary observations.

PubMed

Huellner, Martin W; Appenzeller, Philippe; Kuhn, Félix P; Husmann, Lars; Pietsch, Carsten M; Burger, Irene A; Porto, Miguel; Delso, Gaspar; von Schulthess, Gustav K; Veit-Haibach, Patrick

2014-12-01

To assess the diagnostic performance of whole-body non-contrast material-enhanced positron emission tomography (PET)/magnetic resonance (MR) imaging and PET/computed tomography (CT) for staging and restaging of cancers and provide guidance for modality and sequence selection. This study was approved by the institutional review board and national government authorities. One hundred six consecutive patients (median age, 68 years; 46 female and 60 male patients) referred for staging or restaging of oncologic malignancies underwent whole-body imaging with a sequential trimodality PET/CT/MR system. The MR protocol included short inversion time inversion-recovery ( STIR short inversion time inversion-recovery ), Dixon-type liver accelerated volume acquisition ( LAVA liver accelerated volume acquisition ; GE Healthcare, Waukesha, Wis), and respiratory-gated periodically rotated overlapping parallel lines with enhanced reconstruction ( PROPELLER periodically rotated overlapping parallel lines with enhanced reconstruction ; GE Healthcare) sequences. Primary tumors (n = 43), local lymph node metastases (n = 74), and distant metastases (n = 66) were evaluated for conspicuity (scored 0-4), artifacts (scored 0-2), and reader confidence on PET/CT and PET/MR images. Subanalysis for lung lesions (n = 46) was also performed. Relevant incidental findings with both modalities were compared. Interreader agreement was analyzed with intraclass correlation coefficients and κ statistics. Lesion conspicuity, image artifacts, and incidental findings were analyzed with nonparametric tests. Primary tumors were less conspicuous on STIR short inversion time inversion-recovery (3.08, P = .016) and LAVA liver accelerated volume acquisition (2.64, P = .002) images than on CT images (3.49), while findings with the PROPELLER periodically rotated overlapping parallel lines with enhanced reconstruction sequence (3.70, P = .436) were comparable to those at CT. In distant metastases, the PROPELLER periodically rotated overlapping parallel lines with enhanced reconstruction sequence (3.84) yielded better results than CT (2.88, P < .001). Subanalysis for lung lesions yielded similar results (primary lung tumors: CT, 3.71; STIR short inversion time inversion-recovery , 3.32 [P = .014]; LAVA liver accelerated volume acquisition , 2.52 [P = .002]; PROPELLER periodically rotated overlapping parallel lines with enhanced reconstruction , 3.64 [P = .546]). Readers classified lesions more confidently with PET/MR than PET/CT. However, PET/CT showed more incidental findings than PET/MR (P = .039), especially in the lung (P < .001). MR images had more artifacts than CT images. PET/MR performs comparably to PET/CT in whole-body oncology and neoplastic lung disease, with the use of appropriate sequences. Further studies are needed to define regionalized PET/MR protocols with sequences tailored to specific tumor entities. © RSNA, 2014 Online supplemental material is available for this article.

Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography.

PubMed

Zhang, Tao; Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y; Alley, Marcus T; Lustig, Michael; Pauly, John M; Vasanawala, Shreyas S

2015-10-01

Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography method for depicting abdominal arterial anatomy in young children. With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast-enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast-enhanced MR angiography studies. A radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9-5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries in young children.

A novel 3D Cartesian random sampling strategy for Compressive Sensing Magnetic Resonance Imaging.

PubMed

Valvano, Giuseppe; Martini, Nicola; Santarelli, Maria Filomena; Chiappino, Dante; Landini, Luigi

2015-01-01

In this work we propose a novel acquisition strategy for accelerated 3D Compressive Sensing Magnetic Resonance Imaging (CS-MRI). This strategy is based on a 3D cartesian sampling with random switching of the frequency encoding direction with other K-space directions. Two 3D sampling strategies are presented. In the first strategy, the frequency encoding direction is randomly switched with one of the two phase encoding directions. In the second strategy, the frequency encoding direction is randomly chosen between all the directions of the K-Space. These strategies can lower the coherence of the acquisition, in order to produce reduced aliasing artifacts and to achieve a better image quality after Compressive Sensing (CS) reconstruction. Furthermore, the proposed strategies can reduce the typical smoothing of CS due to the limited sampling of high frequency locations. We demonstrated by means of simulations that the proposed acquisition strategies outperformed the standard Compressive Sensing acquisition. This results in a better quality of the reconstructed images and in a greater achievable acceleration.

A software tool of digital tomosynthesis application for patient positioning in radiotherapy.

PubMed

Yan, Hui; Dai, Jian-Rong

2016-03-08

Digital Tomosynthesis (DTS) is an image modality in reconstructing tomographic images from two-dimensional kV projections covering a narrow scan angles. Comparing with conventional cone-beam CT (CBCT), it requires less time and radiation dose in data acquisition. It is feasible to apply this technique in patient positioning in radiotherapy. To facilitate its clinical application, a software tool was developed and the reconstruction processes were accelerated by graphic process-ing unit (GPU). Two reconstruction and two registration processes are required for DTS application which is different from conventional CBCT application which requires one image reconstruction process and one image registration process. The reconstruction stage consists of productions of two types of DTS. One type of DTS is reconstructed from cone-beam (CB) projections covering a narrow scan angle and is named onboard DTS (ODTS), which represents the real patient position in treatment room. Another type of DTS is reconstructed from digitally reconstructed radiography (DRR) and is named reference DTS (RDTS), which represents the ideal patient position in treatment room. Prior to the reconstruction of RDTS, The DRRs are reconstructed from planning CT using the same acquisition setting of CB projections. The registration stage consists of two matching processes between ODTS and RDTS. The target shift in lateral and longitudinal axes are obtained from the matching between ODTS and RDTS in coronal view, while the target shift in longitudinal and vertical axes are obtained from the matching between ODTS and RDTS in sagittal view. In this software, both DRR and DTS reconstruction algorithms were implemented on GPU environments for acceleration purpose. The comprehensive evaluation of this software tool was performed including geometric accuracy, image quality, registration accuracy, and reconstruction efficiency. The average correlation coefficient between DRR/DTS generated by GPU-based algorithm and CPU-based algorithm is 0.99. Based on the measurements of cube phantom on DTS, the geometric errors are within 0.5 mm in three axes. For both cube phantom and pelvic phantom, the registration errors are within 0.5 mm in three axes. Compared with reconstruction performance of CPU-based algorithms, the performances of DRR and DTS reconstructions are improved by a factor of 15 to 20. A GPU-based software tool was developed for DTS application for patient positioning of radiotherapy. The geometric and registration accuracy met the clinical requirement in patient setup of radiotherapy. The high performance of DRR and DTS reconstruction algorithms was achieved by the GPU-based computation environments. It is a useful software tool for researcher and clinician in evaluating DTS application in patient positioning of radiotherapy.

Shading correction assisted iterative cone-beam CT reconstruction

NASA Astrophysics Data System (ADS)

Yang, Chunlin; Wu, Pengwei; Gong, Shutao; Wang, Jing; Lyu, Qihui; Tang, Xiangyang; Niu, Tianye

2017-11-01

Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images. To overcome this obstacle, we incorporate a shading correction scheme into low-dose CBCT reconstruction and propose a clinically acceptable and stable three-dimensional iterative reconstruction method that is referred to as the shading correction assisted iterative reconstruction. In the proposed method, we modify the TV regularization term by adding a shading compensation image to the reconstructed image to compensate for the shading artifacts while leaving the data fidelity term intact. This compensation image is generated empirically, using image segmentation and low-pass filtering, and updated in the iterative process whenever necessary. When the compensation image is determined, the objective function is minimized using the fast iterative shrinkage-thresholding algorithm accelerated on a graphic processing unit. The proposed method is evaluated using CBCT projection data of the Catphan© 600 phantom and two pelvis patients. Compared with the iterative reconstruction without shading correction, the proposed method reduces the overall CT number error from around 200 HU to be around 25 HU and increases the spatial uniformity by a factor of 20 percent, given the same number of sparsely sampled projections. A clinically acceptable and stable iterative reconstruction algorithm for CBCT is proposed in this paper. Differing from the existing algorithms, this algorithm incorporates a shading correction scheme into the low-dose CBCT reconstruction and achieves more stable optimization path and more clinically acceptable reconstructed image. The method proposed by us does not rely on prior information and thus is practically attractive to the applications of low-dose CBCT imaging in the clinic.

Fast dictionary-based reconstruction for diffusion spectrum imaging.

PubMed

Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar

2013-11-01

Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging

PubMed Central

Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar

2015-01-01

Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466

Real-time photo-magnetic imaging.

PubMed

Nouizi, Farouk; Erkol, Hakan; Luk, Alex; Unlu, Mehmet B; Gulsen, Gultekin

2016-10-01

We previously introduced a new high resolution diffuse optical imaging modality termed, photo-magnetic imaging (PMI). PMI irradiates the object under investigation with near-infrared light and monitors the variations of temperature using magnetic resonance thermometry (MRT). In this paper, we present a real-time PMI image reconstruction algorithm that uses analytic methods to solve the forward problem and assemble the Jacobian matrix much faster. The new algorithm is validated using real MRT measured temperature maps. In fact, it accelerates the reconstruction process by more than 250 times compared to a single iteration of the FEM-based algorithm, which opens the possibility for the real-time PMI.

Block matching sparsity regularization-based image reconstruction for incomplete projection data in computed tomography

NASA Astrophysics Data System (ADS)

Cai, Ailong; Li, Lei; Zheng, Zhizhong; Zhang, Hanming; Wang, Linyuan; Hu, Guoen; Yan, Bin

2018-02-01

In medical imaging many conventional regularization methods, such as total variation or total generalized variation, impose strong prior assumptions which can only account for very limited classes of images. A more reasonable sparse representation frame for images is still badly needed. Visually understandable images contain meaningful patterns, and combinations or collections of these patterns can be utilized to form some sparse and redundant representations which promise to facilitate image reconstructions. In this work, we propose and study block matching sparsity regularization (BMSR) and devise an optimization program using BMSR for computed tomography (CT) image reconstruction for an incomplete projection set. The program is built as a constrained optimization, minimizing the L1-norm of the coefficients of the image in the transformed domain subject to data observation and positivity of the image itself. To solve the program efficiently, a practical method based on the proximal point algorithm is developed and analyzed. In order to accelerate the convergence rate, a practical strategy for tuning the BMSR parameter is proposed and applied. The experimental results for various settings, including real CT scanning, have verified the proposed reconstruction method showing promising capabilities over conventional regularization.

Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.

PubMed

Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Weavers, Paul T; Huston, John; Gray, Erin M; Bernstein, Matt A

2016-06-01

To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med 75:2534-2544, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

SubspaceEM: A Fast Maximum-a-posteriori Algorithm for Cryo-EM Single Particle Reconstruction

PubMed Central

Dvornek, Nicha C.; Sigworth, Fred J.; Tagare, Hemant D.

2015-01-01

Single particle reconstruction methods based on the maximum-likelihood principle and the expectation-maximization (E–M) algorithm are popular because of their ability to produce high resolution structures. However, these algorithms are computationally very expensive, requiring a network of computational servers. To overcome this computational bottleneck, we propose a new mathematical framework for accelerating maximum-likelihood reconstructions. The speedup is by orders of magnitude and the proposed algorithm produces similar quality reconstructions compared to the standard maximum-likelihood formulation. Our approach uses subspace approximations of the cryo-electron microscopy (cryo-EM) data and projection images, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300. PMID:25839831

Accelerated 4D self-gated MRI of tibiofemoral kinematics.

PubMed

Mazzoli, Valentina; Schoormans, Jasper; Froeling, Martijn; Sprengers, Andre M; Coolen, Bram F; Verdonschot, Nico; Strijkers, Gustav J; Nederveen, Aart J

2017-11-01

Anatomical (static) magnetic resonance imaging (MRI) is the most useful imaging technique for the evaluation and assessment of internal derangement of the knee, but does not provide dynamic information and does not allow the study of the interaction of the different tissues during motion. As knee pain is often only experienced during dynamic tasks, the ability to obtain four-dimensional (4D) images of the knee during motion could improve the diagnosis and provide a deeper understanding of the knee joint. In this work, we present a novel approach for dynamic, high-resolution, 4D imaging of the freely moving knee without the need for external triggering. The dominant knee of five healthy volunteers was scanned during a flexion/extension task. To evaluate the effects of non-uniform motion and poor coordination skills on the quality of the reconstructed images, we performed a comparison between fully free movement and movement instructed by a visual cue. The trigger signal for self-gating was extracted using principal component analysis (PCA), and the images were reconstructed using a parallel imaging and compressed sensing reconstruction pipeline. The reconstructed 4D movies were scored for image quality and used to derive bone kinematics through image registration. Using our method, we were able to obtain 4D high-resolution movies of the knee without the need for external triggering hardware. The movies obtained with and without instruction did not differ significantly in terms of image scoring and quantitative values for tibiofemoral kinematics. Our method showed to be robust for the extraction of the self-gating signal even for uninstructed motion. This can make the technique suitable for patients who, as a result of pain, may find it difficult to comply exactly with instructions. Furthermore, bone kinematics can be derived from accelerated MRI without the need for additional hardware for triggering. Copyright © 2017 John Wiley & Sons, Ltd.

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, D; Kang, S; Kim, T

2014-06-01

Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studiesmore » to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)« less

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

PubMed

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Kalman Filter Techniques for Accelerated Cartesian Dynamic Cardiac Imaging

PubMed Central

Feng, Xue; Salerno, Michael; Kramer, Christopher M.; Meyer, Craig H.

2012-01-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories, because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and SNR. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. PMID:22926804

Fast, Accurate and Shift-Varying Line Projections for Iterative Reconstruction Using the GPU

PubMed Central

Pratx, Guillem; Chinn, Garry; Olcott, Peter D.; Levin, Craig S.

2013-01-01

List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach. PMID:19244015

3D Compressed Sensing for Highly Accelerated Hyperpolarized 13C MRSI With In Vivo Applications to Transgenic Mouse Models of Cancer

PubMed Central

Hu, Simon; Lustig, Michael; Balakrishnan, Asha; Larson, Peder E. Z.; Bok, Robert; Kurhanewicz, John; Nelson, Sarah J.; Goga, Andrei; Pauly, John M.; Vigneron, Daniel B.

2010-01-01

High polarization of nuclear spins in liquid state through hyperpolarized technology utilizing dynamic nuclear polarization has enabled the direct monitoring of 13C metabolites in vivo at a high signal-to-noise ratio. Acquisition time limitations due to T1 decay of the hyperpolarized signal require accelerated imaging methods, such as compressed sensing, for optimal speed and spatial coverage. In this paper, the design and testing of a new echo-planar 13C three-dimensional magnetic resonance spectroscopic imaging (MRSI) compressed sensing sequence is presented. The sequence provides up to a factor of 7.53 in acceleration with minimal reconstruction artifacts. The key to the design is employing x and y gradient blips during a fly-back readout to pseudorandomly undersample kf-kx-ky space. The design was validated in simulations and phantom experiments where the limits of undersampling and the effects of noise on the compressed sensing nonlinear reconstruction were tested. Finally, this new pulse sequence was applied in vivo in preclinical studies involving transgenic prostate cancer and transgenic liver cancer murine models to obtain much higher spatial and temporal resolution than possible with conventional echo-planar spectroscopic imaging methods. PMID:20017160

First-pass myocardial perfusion imaging with whole-heart coverage using L1-SPIRiT accelerated variable density spiral trajectories.

PubMed

Yang, Yang; Kramer, Christopher M; Shaw, Peter W; Meyer, Craig H; Salerno, Michael

2016-11-01

To design and evaluate two-dimensional (2D) L1-SPIRiT accelerated spiral pulse sequences for first-pass myocardial perfusion imaging with whole heart coverage capable of measuring eight slices at 2 mm in-plane resolution at heart rates up to 125 beats per minute (BPM). Combinations of five different spiral trajectories and four k-t sampling patterns were retrospectively simulated in 25 fully sampled datasets and reconstructed with L1-SPIRiT to determine the best combination of parameters. Two candidate sequences were prospectively evaluated in 34 human subjects to assess in vivo performance. A dual density broad transition spiral trajectory with either angularly uniform or golden angle in time k-t sampling pattern had the largest structural similarity and smallest root mean square error from the retrospective simulation, and the L1-SPIRiT reconstruction had well-preserved temporal dynamics. In vivo data demonstrated that both of the sampling patterns could produce high quality perfusion images with whole-heart coverage. First-pass myocardial perfusion imaging using accelerated spirals with optimized trajectory and k-t sampling pattern can produce high quality 2D perfusion images with whole-heart coverage at the heart rates up to 125 BPM. Magn Reson Med 76:1375-1387, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

Accelerated Optical Projection Tomography Applied to In Vivo Imaging of Zebrafish

PubMed Central

Correia, Teresa; Yin, Jun; Ramel, Marie-Christine; Andrews, Natalie; Katan, Matilda; Bugeon, Laurence; Dallman, Margaret J.; McGinty, James; Frankel, Paul; French, Paul M. W.; Arridge, Simon

2015-01-01

Optical projection tomography (OPT) provides a non-invasive 3-D imaging modality that can be applied to longitudinal studies of live disease models, including in zebrafish. Current limitations include the requirement of a minimum number of angular projections for reconstruction of reasonable OPT images using filtered back projection (FBP), which is typically several hundred, leading to acquisition times of several minutes. It is highly desirable to decrease the number of required angular projections to decrease both the total acquisition time and the light dose to the sample. This is particularly important to enable longitudinal studies, which involve measurements of the same fish at different time points. In this work, we demonstrate that the use of an iterative algorithm to reconstruct sparsely sampled OPT data sets can provide useful 3-D images with 50 or fewer projections, thereby significantly decreasing the minimum acquisition time and light dose while maintaining image quality. A transgenic zebrafish embryo with fluorescent labelling of the vasculature was imaged to acquire densely sampled (800 projections) and under-sampled data sets of transmitted and fluorescence projection images. The under-sampled OPT data sets were reconstructed using an iterative total variation-based image reconstruction algorithm and compared against FBP reconstructions of the densely sampled data sets. To illustrate the potential for quantitative analysis following rapid OPT data acquisition, a Hessian-based method was applied to automatically segment the reconstructed images to select the vasculature network. Results showed that 3-D images of the zebrafish embryo and its vasculature of sufficient visual quality for quantitative analysis can be reconstructed using the iterative algorithm from only 32 projections—achieving up to 28 times improvement in imaging speed and leading to total acquisition times of a few seconds. PMID:26308086

Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

PubMed Central

Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y.; Alley, Marcus T.; Lustig, Michael; Pauly, John M.; Vasanawala, Shreyas S.

2015-01-01

Background Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. Objective To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast enhanced MR angiography method for depicting abdominal arterial anatomy in young children. Materials and methods With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast enhanced MR angiography studies. An radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Results Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9–5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Conclusion Free-breathing spatiotemporally accelerated 3-D time-resolved contrast enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries for pediatric contrast enhanced MR angiography. PMID:26040509

Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting.

PubMed

Cao, Xiaozhi; Liao, Congyu; Wang, Zhixing; Chen, Ying; Ye, Huihui; He, Hongjian; Zhong, Jianhui

2017-10-01

To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes. A sliding-window (SW) strategy was applied to MRF, in which signal and dictionary matching was conducted between fingerprints consisting of mixed-contrast image series reconstructed from consecutive data frames segmented by a sliding window, and a precalculated mixed-contrast dictionary. The effectiveness and performance of this new method, dubbed SW-MRF, was evaluated in both phantom and in vivo. Error quantifications were conducted on results obtained with various settings of SW reconstruction parameters. Compared with the original MRF strategy, the results of both phantom and in vivo experiments demonstrate that the proposed SW-MRF strategy either provided similar accuracy with reduced acquisition time, or improved accuracy with equal acquisition time. Parametric maps of T 1 , T 2 , and proton density of comparable quality could be achieved with a two-fold or more reduction in acquisition time. The effect of sliding-window width on dictionary sensitivity was also estimated. The novel SW-MRF recovers high quality image frames from highly undersampled MRF data, which enables more robust dictionary matching with reduced numbers of data frames. This time efficiency may facilitate MRF applications in time-critical clinical settings. Magn Reson Med 78:1579-1588, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

PubMed Central

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-01-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate Ki as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting Ki images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit Ki bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source Software for Tomographic Image Reconstruction (STIR) platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced Ki target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D vs. the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10–20 sub-iterations. Moreover, systematic reduction in Ki % bias and improved TBR were observed for gPatlak vs. sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior Ki CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging. PMID:27383991

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-08-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were observed for gPatlak versus sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior K i CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging.

Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering

NASA Astrophysics Data System (ADS)

Wang, Yihan; Lu, Tong; Wan, Wenbo; Liu, Lingling; Zhang, Songhe; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the "compressive sensing" procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.

Sub-aperture switching based ptychographic iterative engine (sasPIE) method for quantitative imaging

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Jiang, Zhilong; Yu, Wei; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-03-01

Though ptychographic iterative engine (PIE) has been widely adopted in the quantitative micro-imaging with various illuminations as visible light, X-ray and electron beam, the mechanical inaccuracy in the raster scanning of the sample relative to the illumination always degrades the reconstruction quality seriously and makes the resolution reached much lower than that determined by the numerical aperture of the optical system. To overcome this disadvantage, the sub-aperture switching based PIE method is proposed: the mechanical scanning in the common PIE is replaced by the sub-aperture switching, and the reconstruction error related to the positioning inaccuracy is completely avoided. The proposed technique remarkably improves the reconstruction quality, reduces the complexity of the experimental setup and fundamentally accelerates the data acquisition and reconstruction.

Supercomputer algorithms for efficient linear octree encoding of three-dimensional brain images.

PubMed

Berger, S B; Reis, D J

1995-02-01

We designed and implemented algorithms for three-dimensional (3-D) reconstruction of brain images from serial sections using two important supercomputer architectures, vector and parallel. These architectures were represented by the Cray YMP and Connection Machine CM-2, respectively. The programs operated on linear octree representations of the brain data sets, and achieved 500-800 times acceleration when compared with a conventional laboratory workstation. As the need for higher resolution data sets increases, supercomputer algorithms may offer a means of performing 3-D reconstruction well above current experimental limits.

A software tool of digital tomosynthesis application for patient positioning in radiotherapy

PubMed Central

Dai, Jian‐Rong

2016-01-01

Digital Tomosynthesis (DTS) is an image modality in reconstructing tomographic images from two‐dimensional kV projections covering a narrow scan angles. Comparing with conventional cone‐beam CT (CBCT), it requires less time and radiation dose in data acquisition. It is feasible to apply this technique in patient positioning in radiotherapy. To facilitate its clinical application, a software tool was developed and the reconstruction processes were accelerated by graphic processing unit (GPU). Two reconstruction and two registration processes are required for DTS application which is different from conventional CBCT application which requires one image reconstruction process and one image registration process. The reconstruction stage consists of productions of two types of DTS. One type of DTS is reconstructed from cone‐beam (CB) projections covering a narrow scan angle and is named onboard DTS (ODTS), which represents the real patient position in treatment room. Another type of DTS is reconstructed from digitally reconstructed radiography (DRR) and is named reference DTS (RDTS), which represents the ideal patient position in treatment room. Prior to the reconstruction of RDTS, The DRRs are reconstructed from planning CT using the same acquisition setting of CB projections. The registration stage consists of two matching processes between ODTS and RDTS. The target shift in lateral and longitudinal axes are obtained from the matching between ODTS and RDTS in coronal view, while the target shift in longitudinal and vertical axes are obtained from the matching between ODTS and RDTS in sagittal view. In this software, both DRR and DTS reconstruction algorithms were implemented on GPU environments for acceleration purpose. The comprehensive evaluation of this software tool was performed including geometric accuracy, image quality, registration accuracy, and reconstruction efficiency. The average correlation coefficient between DRR/DTS generated by GPU‐based algorithm and CPU‐based algorithm is 0.99. Based on the measurements of cube phantom on DTS, the geometric errors are within 0.5 mm in three axes. For both cube phantom and pelvic phantom, the registration errors are within 0.5 mm in three axes. Compared with reconstruction performance of CPU‐based algorithms, the performances of DRR and DTS reconstructions are improved by a factor of 15 to 20. A GPU‐based software tool was developed for DTS application for patient positioning of radiotherapy. The geometric and registration accuracy met the clinical requirement in patient setup of radiotherapy. The high performance of DRR and DTS reconstruction algorithms was achieved by the GPU‐based computation environments. It is a useful software tool for researcher and clinician in evaluating DTS application in patient positioning of radiotherapy. PACS number(s): 87.57.nf PMID:27074482

Experimental study of heavy-ion computed tomography using a scintillation screen and an electron-multiplying charged coupled device camera for human head imaging

NASA Astrophysics Data System (ADS)

Muraishi, Hiroshi; Hara, Hidetake; Abe, Shinji; Yokose, Mamoru; Watanabe, Takara; Takeda, Tohoru; Koba, Yusuke; Fukuda, Shigekazu

2016-03-01

We have developed a heavy-ion computed tomography (IonCT) system using a scintillation screen and an electron-multiplying charged coupled device (EMCCD) camera that can measure a large object such as a human head. In this study, objective with the development of the system was to investigate the possibility of applying this system to heavy-ion treatment planning from the point of view of spatial resolution in a reconstructed image. Experiments were carried out on a rotation phantom using 12C accelerated up to 430 MeV/u by the Heavy-Ion Medical Accelerator in Chiba (HIMAC) at the National Institute of Radiological Sciences (NIRS). We demonstrated that the reconstructed image of an object with a water equivalent thickness (WET) of approximately 18 cm was successfully achieved with the spatial resolution of 1 mm, which would make this IonCT system worth applying to the heavy-ion treatment planning for head and neck cancers.

Deep learning massively accelerates super-resolution localization microscopy.

PubMed

Ouyang, Wei; Aristov, Andrey; Lelek, Mickaël; Hao, Xian; Zimmer, Christophe

2018-06-01

The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PALM, a computational strategy that uses artificial neural networks to reconstruct super-resolution views from sparse, rapidly acquired localization images and/or widefield images. Simulations and experimental imaging of microtubules, nuclear pores, and mitochondria show that high-quality, super-resolution images can be reconstructed from up to two orders of magnitude fewer frames than usually needed, without compromising spatial resolution. Super-resolution reconstructions are even possible from widefield images alone, though adding localization data improves image quality. We demonstrate super-resolution imaging of >1,000 fields of view containing >1,000 cells in ∼3 h, yielding an image spanning spatial scales from ∼20 nm to ∼2 mm. The drastic reduction in acquisition time and sample irradiation afforded by ANNA-PALM enables faster and gentler high-throughput and live-cell super-resolution imaging.

GPU Accelerated Ultrasonic Tomography Using Propagation and Back Propagation Method

DTIC Science & Technology

2015-09-28

the medical imaging field using GPUs has been done for many years. In [1], Copeland et al. used 2D images , obtained by X - ray projections, to...Index Terms— Medical Imaging , Ultrasonic Tomography, GPU, CUDA, Parallel Computing I. INTRODUCTION GRAPHIC Processing Units (GPUs) are computation... Imaging Algorithm The process of reconstructing images from ultrasonic infor- mation starts with the following acoustical wave equation: ∂2 ∂t2 u ( x

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

Accelerated echo planar J-resolved spectroscopic imaging in prostate cancer: a pilot validation of non-linear reconstruction using total variation and maximum entropy.

PubMed

Nagarajan, Rajakumar; Iqbal, Zohaib; Burns, Brian; Wilson, Neil E; Sarma, Manoj K; Margolis, Daniel A; Reiter, Robert E; Raman, Steven S; Thomas, M Albert

2015-11-01

The overlap of metabolites is a major limitation in one-dimensional (1D) spectral-based single-voxel MRS and multivoxel-based MRSI. By combining echo planar spectroscopic imaging (EPSI) with a two-dimensional (2D) J-resolved spectroscopic (JPRESS) sequence, 2D spectra can be recorded in multiple locations in a single slice of prostate using four-dimensional (4D) echo planar J-resolved spectroscopic imaging (EP-JRESI). The goal of the present work was to validate two different non-linear reconstruction methods independently using compressed sensing-based 4D EP-JRESI in prostate cancer (PCa): maximum entropy (MaxEnt) and total variation (TV). Twenty-two patients with PCa with a mean age of 63.8 years (range, 46-79 years) were investigated in this study. A 4D non-uniformly undersampled (NUS) EP-JRESI sequence was implemented on a Siemens 3-T MRI scanner. The NUS data were reconstructed using two non-linear reconstruction methods, namely MaxEnt and TV. Using both TV and MaxEnt reconstruction methods, the following observations were made in cancerous compared with non-cancerous locations: (i) higher mean (choline + creatine)/citrate metabolite ratios; (ii) increased levels of (choline + creatine)/spermine and (choline + creatine)/myo-inositol; and (iii) decreased levels of (choline + creatine)/(glutamine + glutamate). We have shown that it is possible to accelerate the 4D EP-JRESI sequence by four times and that the data can be reliably reconstructed using the TV and MaxEnt methods. The total acquisition duration was less than 13 min and we were able to detect and quantify several metabolites. Copyright © 2015 John Wiley & Sons, Ltd.

Accelerating 4D flow MRI by exploiting vector field divergence regularization.

PubMed

Santelli, Claudio; Loecher, Michael; Busch, Julia; Wieben, Oliver; Schaeffter, Tobias; Kozerke, Sebastian

2016-01-01

To improve velocity vector field reconstruction from undersampled four-dimensional (4D) flow MRI by penalizing divergence of the measured flow field. Iterative image reconstruction in which magnitude and phase are regularized separately in alternating iterations was implemented. The approach allows incorporating prior knowledge of the flow field being imaged. In the present work, velocity data were regularized to reduce divergence, using either divergence-free wavelets (DFW) or a finite difference (FD) method using the ℓ1-norm of divergence and curl. The reconstruction methods were tested on a numerical phantom and in vivo data. Results of the DFW and FD approaches were compared with data obtained with standard compressed sensing (CS) reconstruction. Relative to standard CS, directional errors of vector fields and divergence were reduced by 55-60% and 38-48% for three- and six-fold undersampled data with the DFW and FD methods. Velocity vector displays of the numerical phantom and in vivo data were found to be improved upon DFW or FD reconstruction. Regularization of vector field divergence in image reconstruction from undersampled 4D flow data is a valuable approach to improve reconstruction accuracy of velocity vector fields. © 2014 Wiley Periodicals, Inc.

Single-shot EPI with Nyquist ghost compensation: Interleaved Dual-Echo with Acceleration (IDEA) EPI

PubMed Central

Poser, Benedikt A; Barth, Markus; Goa, Pål-Erik; Deng, Weiran; Stenger, V Andrew

2012-01-01

Echo planar imaging is most commonly used for BOLD fMRI, owing to its sensitivity and acquisition speed. A major problem with EPI is Nyquist (N/2) ghosting, most notably at high field. EPI data are acquired under an oscillating readout gradient and hence vulnerable to gradient imperfections such as eddy current delays and off-resonance effects, as these cause inconsistencies between odd and even k-space lines after time reversal. We propose a straightforward and pragmatic method herein termed Interleaved Dual Echo with Acceleration (IDEA) EPI: Two k-spaces (echoes) are acquired under the positive and negative readout lobes, respectively, by performing phase blips only before alternate readout gradients. From these two k-spaces, two almost entirely ghost free images per shot can be constructed, without need for phase correction. The doubled echo train length can be compensated by parallel imaging and/or partial Fourier acquisition. The two k-spaces can either be complex-averaged during reconstruction, which results in near-perfect cancellation of residual phase errors, or reconstructed into separate images. We demonstrate the efficacy of IDEA EPI and show phantom and in vivo images at both 3 and 7 Tesla. PMID:22411762

Accelerated perturbation-resilient block-iterative projection methods with application to image reconstruction

PubMed Central

Nikazad, T; Davidi, R; Herman, G. T.

2013-01-01

We study the convergence of a class of accelerated perturbation-resilient block-iterative projection methods for solving systems of linear equations. We prove convergence to a fixed point of an operator even in the presence of summable perturbations of the iterates, irrespective of the consistency of the linear system. For a consistent system, the limit point is a solution of the system. In the inconsistent case, the symmetric version of our method converges to a weighted least squares solution. Perturbation resilience is utilized to approximate the minimum of a convex functional subject to the equations. A main contribution, as compared to previously published approaches to achieving similar aims, is a more than an order of magnitude speed-up, as demonstrated by applying the methods to problems of image reconstruction from projections. In addition, the accelerated algorithms are illustrated to be better, in a strict sense provided by the method of statistical hypothesis testing, than their unaccelerated versions for the task of detecting small tumors in the brain from X-ray CT projection data. PMID:23440911

Accelerated perturbation-resilient block-iterative projection methods with application to image reconstruction.

PubMed

Nikazad, T; Davidi, R; Herman, G T

2012-03-01

We study the convergence of a class of accelerated perturbation-resilient block-iterative projection methods for solving systems of linear equations. We prove convergence to a fixed point of an operator even in the presence of summable perturbations of the iterates, irrespective of the consistency of the linear system. For a consistent system, the limit point is a solution of the system. In the inconsistent case, the symmetric version of our method converges to a weighted least squares solution. Perturbation resilience is utilized to approximate the minimum of a convex functional subject to the equations. A main contribution, as compared to previously published approaches to achieving similar aims, is a more than an order of magnitude speed-up, as demonstrated by applying the methods to problems of image reconstruction from projections. In addition, the accelerated algorithms are illustrated to be better, in a strict sense provided by the method of statistical hypothesis testing, than their unaccelerated versions for the task of detecting small tumors in the brain from X-ray CT projection data.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

The effects of navigator distortion and noise level on interleaved EPI DWI reconstruction: a comparison between image- and k-space-based method.

PubMed

Dai, Erpeng; Zhang, Zhe; Ma, Xiaodong; Dong, Zijing; Li, Xuesong; Xiong, Yuhui; Yuan, Chun; Guo, Hua

2018-03-23

To study the effects of 2D navigator distortion and noise level on interleaved EPI (iEPI) DWI reconstruction, using either the image- or k-space-based method. The 2D navigator acquisition was adjusted by reducing its echo spacing in the readout direction and undersampling in the phase encoding direction. A POCS-based reconstruction using image-space sampling function (IRIS) algorithm (POCSIRIS) was developed to reduce the impact of navigator distortion. POCSIRIS was then compared with the original IRIS algorithm and a SPIRiT-based k-space algorithm, under different navigator distortion and noise levels. Reducing the navigator distortion can improve the reconstruction of iEPI DWI. The proposed POCSIRIS and SPIRiT-based algorithms are more tolerable to different navigator distortion levels, compared to the original IRIS algorithm. SPIRiT may be hindered by low SNR of the navigator. Multi-shot iEPI DWI reconstruction can be improved by reducing the 2D navigator distortion. Different reconstruction methods show variable sensitivity to navigator distortion or noise levels. Furthermore, the findings can be valuable in applications such as simultaneous multi-slice accelerated iEPI DWI and multi-slab diffusion imaging. © 2018 International Society for Magnetic Resonance in Medicine.

High-Frequency Subband Compressed Sensing MRI Using Quadruplet Sampling

PubMed Central

Sung, Kyunghyun; Hargreaves, Brian A

2013-01-01

Purpose To presents and validates a new method that formalizes a direct link between k-space and wavelet domains to apply separate undersampling and reconstruction for high- and low-spatial-frequency k-space data. Theory and Methods High- and low-spatial-frequency regions are defined in k-space based on the separation of wavelet subbands, and the conventional compressed sensing (CS) problem is transformed into one of localized k-space estimation. To better exploit wavelet-domain sparsity, CS can be used for high-spatial-frequency regions while parallel imaging can be used for low-spatial-frequency regions. Fourier undersampling is also customized to better accommodate each reconstruction method: random undersampling for CS and regular undersampling for parallel imaging. Results Examples using the proposed method demonstrate successful reconstruction of both low-spatial-frequency content and fine structures in high-resolution 3D breast imaging with a net acceleration of 11 to 12. Conclusion The proposed method improves the reconstruction accuracy of high-spatial-frequency signal content and avoids incoherent artifacts in low-spatial-frequency regions. This new formulation also reduces the reconstruction time due to the smaller problem size. PMID:23280540

QR-decomposition based SENSE reconstruction using parallel architecture.

PubMed

Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

2018-04-01

Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Accelerated proton echo planar spectroscopic imaging (PEPSI) using GRAPPA with a 32-channel phased-array coil.

PubMed

Tsai, Shang-Yueh; Otazo, Ricardo; Posse, Stefan; Lin, Yi-Ru; Chung, Hsiao-Wen; Wald, Lawrence L; Wiggins, Graham C; Lin, Fa-Hsuan

2008-05-01

Parallel imaging has been demonstrated to reduce the encoding time of MR spectroscopic imaging (MRSI). Here we investigate up to 5-fold acceleration of 2D proton echo planar spectroscopic imaging (PEPSI) at 3T using generalized autocalibrating partial parallel acquisition (GRAPPA) with a 32-channel coil array, 1.5 cm(3) voxel size, TR/TE of 15/2000 ms, and 2.1 Hz spectral resolution. Compared to an 8-channel array, the smaller RF coil elements in this 32-channel array provided a 3.1-fold and 2.8-fold increase in signal-to-noise ratio (SNR) in the peripheral region and the central region, respectively, and more spatial modulated information. Comparison of sensitivity-encoding (SENSE) and GRAPPA reconstruction using an 8-channel array showed that both methods yielded similar quantitative metabolite measures (P > 0.1). Concentration values of N-acetyl-aspartate (NAA), total creatine (tCr), choline (Cho), myo-inositol (mI), and the sum of glutamate and glutamine (Glx) for both methods were consistent with previous studies. Using the 32-channel array coil the mean Cramer-Rao lower bounds (CRLB) were less than 8% for NAA, tCr, and Cho and less than 15% for mI and Glx at 2-fold acceleration. At 4-fold acceleration the mean CRLB for NAA, tCr, and Cho was less than 11%. In conclusion, the use of a 32-channel coil array and GRAPPA reconstruction can significantly reduce the measurement time for mapping brain metabolites. (c) 2008 Wiley-Liss, Inc.

Interior tomographic imaging for x-ray coherent scattering (Conference Presentation)

NASA Astrophysics Data System (ADS)

Pang, Sean; Zhu, Zheyuan

2017-05-01

Conventional computed tomography reconstructs the attenuation only high-dimensional images. Coherent scatter computed tomography, which reconstructs the angular dependent scattering profiles of 3D objects, can provide molecular signatures that improves the accuracy of material identification and classification. Coherent scatter tomography are traditionally acquired by setups similar to x-ray powder diffraction machine; a collimated source in combination with 2D or 1D detector collimation in order to localize the scattering point. In addition, the coherent scatter cross-section is often 3 orders of magnitude lower than that of the absorption cross-section for the same material. Coded aperture and structured illumination approaches has been shown to greatly improve the collection efficiency. In many applications, especially in security imaging and medical diagnosis, fast and accurate identification of the material composition of a small volume within the whole object would lead to an accelerated imaging procedure and reduced radiation dose. Here, we report an imaging method to reconstruct the material coherent scatter profile within a small volume. The reconstruction along one radial direction can reconstruct a scalar coherent scattering tomographic image. Our methods takes advantage of the finite support of the scattering profile in small angle regime. Our system uses a pencil beam setup without using any detector side collimation. Coherent scatter profile of a 10 mm scattering sample embedded in a 30 mm diameter phantom was reconstructed. The setup has small form factor and is suitable for various portable non-destructive detection applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beaudry, J.; Bergman, A.; British Columbia Cancer Agency - Vancouver Centre, Vancouver, BC

Lung tumours move due to respiratory motion. This is managed during planning by acquiring a 4DCT and capturing the excursion of the GTV (gross tumour volume) throughout the breathing cycle within an IGTV (Internal Gross Tumour Volume) contour. Patients undergo a verification cone-beam CT (CBCT) scan immediately prior to treatment. 3D reconstructed images do not consider tumour motion, resulting in image artefacts, such as blurring. This may lead to difficulty in identifying the tumour on reconstructed images. It would be valuable to create a 4DCBCT reconstruction of the tumour motion to confirm that does indeed remain within the planned IGTV.more » CBCT projections of a Quasar Respiratory Motion Phantom are acquired in Treatment mode (half-fan scan) on a Varian TrueBeam accelerator. This phantom contains a mobile, low-density lung insert with an embedded 3cm diameter tumour object. It is programmed to create a 15s periodic, 2cm (sup/inf) displacement. A Varian Real-time Position Management (RPM) tracking-box is placed on the phantom breathing platform. Breathing phase information is automatically integrated into the projection image files. Using in-house Matlab programs and RTK (Reconstruction Tool Kit) open-source toolboxes, the projections are re-binned into 10 phases and a 4DCBCT scan reconstructed. The planning IGTV is registered to the 4DCBCT and the tumour excursion is verified to remain within the planned contour. This technique successfully reconstructs 4DCBCT images using clinical modes for a breathing phantom. UBC-BCCA ethics approval has been obtained to perform 4DCBCT reconstructions on lung patients (REB#H12-00192). Clinical images will be accrued starting April 2014.« less

Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

Statistically based iterative approaches for image reconstruction have gained much attention in medical imaging. An accurate system matrix that defines the mapping from the image space to the data space is the key to high-resolution image reconstruction. However, an accurate system matrix is often associated with high computational cost and huge storage requirement. Here we present a method to address this problem by using sparse matrix factorization and parallel computing on a graphic processing unit (GPU).We factor the accurate system matrix into three sparse matrices: a sinogram blurring matrix, a geometric projection matrix, and an image blurring matrix. The sinogram blurring matrix models the detector response. The geometric projection matrix is based on a simple line integral model. The image blurring matrix is to compensate for the line-of-response (LOR) degradation due to the simplified geometric projection matrix. The geometric projection matrix is precomputed, while the sinogram and image blurring matrices are estimated by minimizing the difference between the factored system matrix and the original system matrix. The resulting factored system matrix has much less number of nonzero elements than the original system matrix and thus substantially reduces the storage and computation cost. The smaller size also allows an efficient implement of the forward and back projectors on GPUs, which have limited amount of memory. Our simulation studies show that the proposed method can dramatically reduce the computation cost of high-resolution iterative image reconstruction. The proposed technique is applicable to image reconstruction for different imaging modalities, including x-ray CT, PET, and SPECT.

MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance

PubMed Central

2014-01-01

Background Computer simulations are important for validating novel image acquisition and reconstruction strategies. In cardiovascular magnetic resonance (CMR), numerical simulations need to combine anatomical information and the effects of cardiac and/or respiratory motion. To this end, a framework for realistic CMR simulations is proposed and its use for image reconstruction from undersampled data is demonstrated. Methods The extended Cardiac-Torso (XCAT) anatomical phantom framework with various motion options was used as a basis for the numerical phantoms. Different tissue, dynamic contrast and signal models, multiple receiver coils and noise are simulated. Arbitrary trajectories and undersampled acquisition can be selected. The utility of the framework is demonstrated for accelerated cine and first-pass myocardial perfusion imaging using k-t PCA and k-t SPARSE. Results MRXCAT phantoms allow for realistic simulation of CMR including optional cardiac and respiratory motion. Example reconstructions from simulated undersampled k-t parallel imaging demonstrate the feasibility of simulated acquisition and reconstruction using the presented framework. Myocardial blood flow assessment from simulated myocardial perfusion images highlights the suitability of MRXCAT for quantitative post-processing simulation. Conclusion The proposed MRXCAT phantom framework enables versatile and realistic simulations of CMR including breathhold and free-breathing acquisitions. PMID:25204441

UNFOLD-SENSE: a parallel MRI method with self-calibration and artifact suppression.

PubMed

Madore, Bruno

2004-08-01

This work aims at improving the performance of parallel imaging by using it with our "unaliasing by Fourier-encoding the overlaps in the temporal dimension" (UNFOLD) temporal strategy. A self-calibration method called "self, hybrid referencing with UNFOLD and GRAPPA" (SHRUG) is presented. SHRUG combines the UNFOLD-based sensitivity mapping strategy introduced in the TSENSE method by Kellman et al. (5), with the strategy introduced in the GRAPPA method by Griswold et al. (10). SHRUG merges the two approaches to alleviate their respective limitations, and provides fast self-calibration at any given acceleration factor. UNFOLD-SENSE further includes an UNFOLD artifact suppression scheme to significantly suppress artifacts and amplified noise produced by parallel imaging. This suppression scheme, which was published previously (4), is related to another method that was presented independently as part of TSENSE. While the two are equivalent at accelerations < or = 2.0, the present approach is shown here to be significantly superior at accelerations > 2.0, with up to double the artifact suppression at high accelerations. Furthermore, a slight modification of Cartesian SENSE is introduced, which allows departures from purely Cartesian sampling grids. This technique, termed variable-density SENSE (vdSENSE), allows the variable-density data required by SHRUG to be reconstructed with the simplicity and fast processing of Cartesian SENSE. UNFOLD-SENSE is given by the combination of SHRUG for sensitivity mapping, vdSENSE for reconstruction, and UNFOLD for artifact/amplified noise suppression. The method was implemented, with online reconstruction, on both an SSFP and a myocardium-perfusion sequence. The results from six patients scanned with UNFOLD-SENSE are presented.

Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms.

PubMed

Liu, Jing; Koskas, Louise; Faraji, Farshid; Kao, Evan; Wang, Yan; Haraldsson, Henrik; Kefayati, Sarah; Zhu, Chengcheng; Ahn, Sinyeob; Laub, Gerhard; Saloner, David

2018-04-01

To evaluate an accelerated 4D flow MRI method that provides high temporal resolution in a clinically feasible acquisition time for intracranial velocity imaging. Accelerated 4D flow MRI was developed by using a pseudo-random variable-density Cartesian undersampling strategy (CIRCUS) with the combination of k-t, parallel imaging and compressed sensing image reconstruction techniques (k-t SPARSE-SENSE). Four-dimensional flow data were acquired on five healthy volunteers and eight patients with intracranial aneurysms using CIRCUS (acceleration factor of R = 4, termed CIRCUS4) and GRAPPA (R = 2, termed GRAPPA2) as the reference method. Images with three times higher temporal resolution (R = 12, CIRCUS12) were also reconstructed from the same acquisition as CIRCUS4. Qualitative and quantitative image assessment was performed on the images acquired with different methods, and complex flow patterns in the aneurysms were identified and compared. Four-dimensional flow MRI with CIRCUS was achieved in 5 min and allowed further improved temporal resolution of <30 ms. Volunteer studies showed similar qualitative and quantitative evaluation obtained with the proposed approach compared to the reference (overall image scores: GRAPPA2 3.2 ± 0.6; CIRCUS4 3.1 ± 0.7; CIRCUS12 3.3 ± 0.4; difference of the peak velocities: -3.83 ± 7.72 cm/s between CIRCUS4 and GRAPPA2, -1.72 ± 8.41 cm/s between CIRCUS12 and GRAPPA2). In patients with intracranial aneurysms, the higher temporal resolution improved capturing of the flow features in intracranial aneurysms (pathline visualization scores: GRAPPA2 2.2 ± 0.2; CIRCUS4 2.5 ± 0.5; CIRCUS12 2.7 ± 0.6). The proposed rapid 4D flow MRI with a high temporal resolution is a promising tool for evaluating intracranial aneurysms in a clinically feasible acquisition time.

Iterative feature refinement for accurate undersampled MR image reconstruction

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy

NASA Astrophysics Data System (ADS)

Bailleul, J.; Simon, B.; Debailleul, M.; Liu, H.; Haeberlé, O.

2012-06-01

Phase microscopy techniques regained interest in allowing for the observation of unprepared specimens with excellent temporal resolution. Tomographic diffractive microscopy is an extension of holographic microscopy which permits 3D observations with a finer resolution than incoherent light microscopes. Specimens are imaged by a series of 2D holograms: their accumulation progressively fills the range of frequencies of the specimen in Fourier space. A 3D inverse FFT eventually provides a spatial image of the specimen. Consequently, acquisition then reconstruction are mandatory to produce an image that could prelude real-time control of the observed specimen. The MIPS Laboratory has built a tomographic diffractive microscope with an unsurpassed 130nm resolution but a low imaging speed - no less than one minute. Afterwards, a high-end PC reconstructs the 3D image in 20 seconds. We now expect an interactive system providing preview images during the acquisition for monitoring purposes. We first present a prototype implementing this solution on CPU: acquisition and reconstruction are tied in a producer-consumer scheme, sharing common data into CPU memory. Then we present a prototype dispatching some reconstruction tasks to GPU in order to take advantage of SIMDparallelization for FFT and higher bandwidth for filtering operations. The CPU scheme takes 6 seconds for a 3D image update while the GPU scheme can go down to 2 or > 1 seconds depending on the GPU class. This opens opportunities for 4D imaging of living organisms or crystallization processes. We also consider the relevance of GPU for 3D image interaction in our specific conditions.

Joint Spatial-Spectral Reconstruction and k-t Spirals for Accelerated 2D Spatial/1D Spectral Imaging of 13C Dynamics

PubMed Central

Gordon, Jeremy W.; Niles, David J.; Fain, Sean B.; Johnson, Kevin M.

2014-01-01

Purpose To develop a novel imaging technique to reduce the number of excitations and required scan time for hyperpolarized 13C imaging. Methods A least-squares based optimization and reconstruction is developed to simultaneously solve for both spatial and spectral encoding. By jointly solving both domains, spectral imaging can potentially be performed with a spatially oversampled single echo spiral acquisition. Digital simulations, phantom experiments, and initial in vivo hyperpolarized [1-13C]pyruvate experiments were performed to assess the performance of the algorithm as compared to a multi-echo approach. Results Simulations and phantom data indicate that accurate single echo imaging is possible when coupled with oversampling factors greater than six (corresponding to a worst case of pyruvate to metabolite ratio < 9%), even in situations of substantial T2* decay and B0 heterogeneity. With lower oversampling rates, two echoes are required for similar accuracy. These results were confirmed with in vivo data experiments, showing accurate single echo spectral imaging with an oversampling factor of 7 and two echo imaging with an oversampling factor of 4. Conclusion The proposed k-t approach increases data acquisition efficiency by reducing the number of echoes required to generate spectroscopic images, thereby allowing accelerated acquisition speed, preserved polarization, and/or improved temporal or spatial resolution. Magn Reson Med PMID:23716402

List-mode PET image reconstruction for motion correction using the Intel XEON PHI co-processor

NASA Astrophysics Data System (ADS)

Ryder, W. J.; Angelis, G. I.; Bashar, R.; Gillam, J. E.; Fulton, R.; Meikle, S.

2014-03-01

List-mode image reconstruction with motion correction is computationally expensive, as it requires projection of hundreds of millions of rays through a 3D array. To decrease reconstruction time it is possible to use symmetric multiprocessing computers or graphics processing units. The former can have high financial costs, while the latter can require refactoring of algorithms. The Xeon Phi is a new co-processor card with a Many Integrated Core architecture that can run 4 multiple-instruction, multiple data threads per core with each thread having a 512-bit single instruction, multiple data vector register. Thus, it is possible to run in the region of 220 threads simultaneously. The aim of this study was to investigate whether the Xeon Phi co-processor card is a viable alternative to an x86 Linux server for accelerating List-mode PET image reconstruction for motion correction. An existing list-mode image reconstruction algorithm with motion correction was ported to run on the Xeon Phi coprocessor with the multi-threading implemented using pthreads. There were no differences between images reconstructed using the Phi co-processor card and images reconstructed using the same algorithm run on a Linux server. However, it was found that the reconstruction runtimes were 3 times greater for the Phi than the server. A new version of the image reconstruction algorithm was developed in C++ using OpenMP for mutli-threading and the Phi runtimes decreased to 1.67 times that of the host Linux server. Data transfer from the host to co-processor card was found to be a rate-limiting step; this needs to be carefully considered in order to maximize runtime speeds. When considering the purchase price of a Linux workstation with Xeon Phi co-processor card and top of the range Linux server, the former is a cost-effective computation resource for list-mode image reconstruction. A multi-Phi workstation could be a viable alternative to cluster computers at a lower cost for medical imaging applications.

Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection

PubMed Central

Lloyd, David F.A.; Price, Anthony N.; Kuklisova Murgasova, Maria; Aljabar, Paul; Malik, Shaihan J.; Lohezic, Maelene; Rutherford, Mary A.; Pushparajah, Kuberan; Razavi, Reza; Hajnal, Joseph V.

2017-01-01

Purpose Development of a MRI acquisition and reconstruction strategy to depict fetal cardiac anatomy in the presence of maternal and fetal motion. Methods The proposed strategy involves i) acquisition and reconstruction of highly accelerated dynamic MRI, followed by image‐based ii) cardiac synchronization, iii) motion correction, iv) outlier rejection, and finally v) cardiac cine reconstruction. Postprocessing entirely was automated, aside from a user‐defined region of interest delineating the fetal heart. The method was evaluated in 30 mid‐ to late gestational age singleton pregnancies scanned without maternal breath‐hold. Results The combination of complementary acquisition/reconstruction and correction/rejection steps in the pipeline served to improve the quality of the reconstructed 2D cine images, resulting in increased visibility of small, dynamic anatomical features. Artifact‐free cine images successfully were produced in 36 of 39 acquired data sets; prolonged general fetal movements precluded processing of the remaining three data sets. Conclusions The proposed method shows promise as a motion‐tolerant framework to enable further detail in MRI studies of the fetal heart and great vessels. Processing data in image‐space allowed for spatial and temporal operations to be applied to the fetal heart in isolation, separate from extraneous changes elsewhere in the field of view. Magn Reson Med 79:327–338, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:28370252

SU-E-J-29: Automatic Image Registration Performance of Three IGRT Systems for Prostate Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barber, J; University of Sydney, Sydney, NSW; Sykes, J

Purpose: To compare the performance of an automatic image registration algorithm on image sets collected on three commercial image guidance systems, and explore its relationship with imaging parameters such as dose and sharpness. Methods: Images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on the CBCT systems of Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings; and MVCT on a Tomotherapy Hi-ART accelerator with a range of pitch. Using the 6D correlation ratio algorithm of XVI, each image was registered to a mask of the prostate volume with a 5 mm expansion.more » Registrations were repeated 100 times, with random initial offsets introduced to simulate daily matching. Residual registration errors were calculated by correcting for the initial phantom set-up error. Automatic registration was also repeated after reconstructing images with different sharpness filters. Results: All three systems showed good registration performance, with residual translations <0.5mm (1σ) for typical clinical dose and reconstruction settings. Residual rotational error had larger range, with 0.8°, 1.2° and 1.9° for 1σ in XVI, OBI and Tomotherapy respectively. The registration accuracy of XVI images showed a strong dependence on imaging dose, particularly below 4mGy. No evidence of reduced performance was observed at the lowest dose settings for OBI and Tomotherapy, but these were above 4mGy. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 10% of registrations. Changing the sharpness of image reconstruction had no significant effect on registration performance. Conclusions: Using the present automatic image registration algorithm, all IGRT systems tested provided satisfactory registrations for clinical use, within a normal range of acquisition settings.« less

Efficient radial tagging CMR exam: A coherent k-space reading and image reconstruction approach.

PubMed

Golshani, Shokoufeh; Nasiraei-Moghaddam, Abbas

2017-04-01

Cardiac MR tagging techniques, which facilitate the strain evaluation, have not yet been widely adopted in clinics due to inefficiencies in acquisition and postprocessing. This problem may be alleviated by exploiting the coherency in the three steps of tagging: preparation, acquisition, and reconstruction. Herein, we propose a fully polar-based tagging approach that may lead to real-time strain mapping. Radial readout trajectories were used to acquire radial tagging images and a Hankel-based algorithm, referred to as Polar Fourier Transform (PFT), has been adapted for reconstruction of the acquired raw data. In both phantom and human subjects, the overall performance of the method was investigated against radial undersampling and compared with the conventional reconstruction methods. Radially tagged images were reconstructed by the proposed PFT method from as few as 24 spokes with normalized root-mean-square-error of less than 3%. The reconstructed images showed a central focusing behavior, where the undersampling effects were pushed to the peripheral areas out of the central region of interest. Comparing the results with the re-gridding reconstruction technique, superior image quality and high robustness of the method were further established. In addition, a relative increase of 68 ± 2.5% in tagline sharpness was achieved for the PFT images and also higher tagging contrast (72 ± 5.6%), resulted from the well-tolerated undersampling artifacts, was observed in all reconstructions. The proposed approach led to the acceleration of the acquisition process, which was evaluated for up to eight-fold retrospectively from the fully sampled data. This is promising toward real-time imaging, and in contrast to iterative techniques, the method is consistent with online reconstruction. Magn Reson Med 77:1459-1472, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

SU-E-J-167: Improvement of Time-Ordered Four Dimensional Cone-Beam CT; Image Mosaicing with Real and Virtual Projections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakano, M; Kida, S; Masutani, Y

2014-06-01

Purpose: In the previous study, we developed time-ordered fourdimensional (4D) cone-beam CT (CBCT) technique to visualize nonperiodic organ motion, such as peristaltic motion of gastrointestinal organs and adjacent area, using half-scan reconstruction method. One important obstacle was that truncation of projection was caused by asymmetric location of flat-panel detector (FPD) in order to cover whole abdomen or pelvis in one rotation. In this study, we propose image mosaicing to extend projection data to make possible to reconstruct full field-of-view (FOV) image using half-scan reconstruction. Methods: The projections of prostate cancer patients were acquired using the X-ray Volume Imaging system (XVI,more » version 4.5) on Synergy linear accelerator system (Elekta, UK). The XVI system has three options of FOV, S, M and L, and M FOV was chosen for pelvic CBCT acquisition, with a FPD panel 11.5 cm offset. The method to produce extended projections consists of three main steps: First, normal three-dimensional (3D) reconstruction which contains whole pelvis was implemented using real projections. Second, virtual projections were produced by reprojection process of the reconstructed 3D image. Third, real and virtual projections in each angle were combined into one extended mosaic projection. Then, 4D CBCT images were reconstructed using our inhouse reconstruction software based on Feldkamp, Davis and Kress algorithm. The angular range of each reconstruction phase in the 4D reconstruction was 180 degrees, and the range moved as time progressed. Results: Projection data were successfully extended without discontinuous boundary between real and virtual projections. Using mosaic projections, 4D CBCT image sets were reconstructed without artifacts caused by the truncation, and thus, whole pelvis was clearly visible. Conclusion: The present method provides extended projections which contain whole pelvis. The presented reconstruction method also enables time-ordered 4D CBCT reconstruction of organs with non-periodic motion with full FOV without projection-truncation artifacts. This work was partly supported by the JSPS Core-to-Core Program(No. 23003). This work was partly supported by JSPS KAKENHI 24234567.« less

An implementation of the NiftyRec medical imaging library for PIXE-tomography reconstruction

NASA Astrophysics Data System (ADS)

Michelet, C.; Barberet, P.; Desbarats, P.; Giovannelli, J.-F.; Schou, C.; Chebil, I.; Delville, M.-H.; Gordillo, N.; Beasley, D. G.; Devès, G.; Moretto, P.; Seznec, H.

2017-08-01

A new development of the TomoRebuild software package is presented, including ;thick sample; correction for non linear X-ray production (NLXP) and X-ray absorption (XA). As in the previous versions, C++ programming with standard libraries was used for easier portability. Data reduction requires different steps which may be run either from a command line instruction or via a user friendly interface, developed as a portable Java plugin in ImageJ. All experimental and reconstruction parameters can be easily modified, either directly in the ASCII parameter files or via the ImageJ interface. A detailed user guide in English is provided. Sinograms and final reconstructed images are generated in usual binary formats that can be read by most public domain graphic softwares. New MLEM and OSEM methods are proposed, using optimized methods from the NiftyRec medical imaging library. An overview of the different medical imaging methods that have been used for ion beam microtomography applications is presented. In TomoRebuild, PIXET data reduction is performed for each chemical element independently and separately from STIMT, except for two steps where the fusion of STIMT and PIXET data is required: the calculation of the correction matrix and the normalization of PIXET data to obtain mass fraction distributions. Correction matrices for NLXP and XA are calculated using procedures extracted from the DISRA code, taking into account a large X-ray detection solid angle. For this, the 3D STIMT mass density distribution is used, considering a homogeneous global composition. A first example of PIXET experiment using two detectors is presented. Reconstruction results are compared and found in good agreement between different codes: FBP, NiftyRec MLEM and OSEM of the TomoRebuild software package, the original DISRA, its accelerated version provided in JPIXET and the accelerated MLEM version of JPIXET, with or without correction.

Development Of A Flash X-Ray Scanner For Stereoradiography And CT

NASA Astrophysics Data System (ADS)

Endorf, Robert J.; DiBianca, Frank A.; Fritsch, Daniel S.; Liu, Wen-Ching; Burns, Charles B.

1989-05-01

We are developing a flash x-ray scanner for stereoradiography and CT which will be able to produce a stereoradiograph in 30 to 70 ns and a complete CT scan in one microsecond. This type of imaging device will be valuable in studying high speed processes, high acceleration, and traumatic events. We have built a two channel flash x-ray system capable of producing stereo radiographs with stereo angles of from 15 to 165 degrees. The dynamic and static Miff 's for the flash x-ray system were measured and compared with similar MIT's measured for a conventional medical x-ray system. We have written and tested a stereo reconstruction algorithm to determine three dimensional space points from corresponding points in the two stereo images. To demonstrate the ability of the system to image traumatic events, a radiograph was obtained of a bone undergoing a fracture. The effects of accelerations of up to 600 g were examined on radiographs taken of human kidney tissue samples in a rapidly rotating centrifuge. Feasibility studies of CT reconstruction have been performed by making simulated Cr images of various phantoms for larger flash x-ray systems of from 8 to 29 flash x-ray tubes.

Coil Compression for Accelerated Imaging with Cartesian Sampling

PubMed Central

Zhang, Tao; Pauly, John M.; Vasanawala, Shreyas S.; Lustig, Michael

2012-01-01

MRI using receiver arrays with many coil elements can provide high signal-to-noise ratio and increase parallel imaging acceleration. At the same time, the growing number of elements results in larger datasets and more computation in the reconstruction. This is of particular concern in 3D acquisitions and in iterative reconstructions. Coil compression algorithms are effective in mitigating this problem by compressing data from many channels into fewer virtual coils. In Cartesian sampling there often are fully sampled k-space dimensions. In this work, a new coil compression technique for Cartesian sampling is presented that exploits the spatially varying coil sensitivities in these non-subsampled dimensions for better compression and computation reduction. Instead of directly compressing in k-space, coil compression is performed separately for each spatial location along the fully-sampled directions, followed by an additional alignment process that guarantees the smoothness of the virtual coil sensitivities. This important step provides compatibility with autocalibrating parallel imaging techniques. Its performance is not susceptible to artifacts caused by a tight imaging fieldof-view. High quality compression of in-vivo 3D data from a 32 channel pediatric coil into 6 virtual coils is demonstrated. PMID:22488589

Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging.

PubMed

Zhou, Ruixi; Huang, Wei; Yang, Yang; Chen, Xiao; Weller, Daniel S; Kramer, Christopher M; Kozerke, Sebastian; Salerno, Michael

2018-02-01

Cardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging. A simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists. In the phantom experiments, images reconstructed with the MC strategy had higher SSIM (p < 0.01) and lower RMSE (p < 0.01) in the presence of respiratory motion. For patient studies, the MC strategy improved k-t PCA and k-t SLR reconstruction image quality (p < 0.01). The performance of k-t SLR without motion correction demonstrated improved image quality as compared to k-t PCA in the setting of respiratory motion (p < 0.01), while with motion correction there is a trend of better performance in k-t SLR as compared with motion corrected k-t PCA. Our simple and robust rigid motion compensation strategy greatly reduces motion artifacts and improves image quality for standard k-t PCA and k-t SLR techniques in setting of respiratory motion due to imperfect breath-holding.

A Bayesian Model for Highly Accelerated Phase-Contrast MRI

PubMed Central

Rich, Adam; Potter, Lee C.; Jin, Ning; Ash, Joshua; Simonetti, Orlando P.; Ahmad, Rizwan

2015-01-01

Purpose Phase-contrast magnetic resonance imaging (PC-MRI) is a noninvasive tool to assess cardiovascular disease by quantifying blood flow; however, low data acquisition efficiency limits the spatial and temporal resolutions, real-time application, and extensions to 4D flow imaging in clinical settings. We propose a new data processing approach called Reconstructing Velocity Encoded MRI with Approximate message passing aLgorithms (ReVEAL) that accelerates the acquisition by exploiting data structure unique to PC-MRI. Theory and Methods ReVEAL models physical correlations across space, time, and velocity encodings. The proposed Bayesian approach exploits the relationships in both magnitude and phase among velocity encodings. A fast iterative recovery algorithm is introduced based on message passing. For validation, prospectively undersampled data are processed from a pulsatile flow phantom and five healthy volunteers. Results ReVEAL is in good agreement, quantified by peak velocity and stroke volume (SV), with reference data for acceleration rates R ≤ 10. For SV, Pearson r ≥ 0.996 for phantom imaging (n = 24) and r ≥ 0.956 for prospectively accelerated in vivo imaging (n = 10) for R ≤ 10. Conclusion ReVEAL enables accurate quantification of blood flow from highly undersampled data. The technique is extensible to 4D flow imaging, where higher acceleration may be possible due to additional redundancy. PMID:26444911

Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU.

PubMed

Pang, Wai-Man; Qin, Jing; Lu, Yuqiang; Xie, Yongming; Chui, Chee-Kong; Heng, Pheng-Ann

2011-03-01

To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU. Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation by combining CUDA shared memory. We utilize the independence of each ray and voxel on both techniques to design CUDA kernel to represent a ray in the projection and a voxel in the back-projection respectively. Thus, significant parallelization and performance boost can be achieved. For motion compensation, we rectify each ray's direction during the projection and back-projection stages based on a known motion vector field. Extensive experiments demonstrate the proposed techniques can provide faster reconstruction without compromising image quality. The process rate is nearly 100 projections s (-1), and it is about 150 times faster than a CPU-based SART. The reconstructed image is compared against ground truth visually and quantitatively by peak signal-to-noise ratio (PSNR) and line profiles. We further evaluate the reconstruction quality using quantitative metrics such as signal-to-noise ratio (SNR) and mean-square-error (MSE). All these reveal that satisfactory results are achieved. The effects of major parameters such as ray sampling interval and relaxation parameter are also investigated by a series of experiments. A simulated dataset is used for testing the effectiveness of our motion compensation technique. The results demonstrate our reconstructed volume can eliminate undesirable artifacts like blurring. Our proposed method has potential to realize instantaneous presentation of 3D CT volume to physicians once the projection data are acquired.

Fast direct fourier reconstruction of radial and PROPELLER MRI data using the chirp transform algorithm on graphics hardware.

PubMed

Feng, Yanqiu; Song, Yanli; Wang, Cong; Xin, Xuegang; Feng, Qianjin; Chen, Wufan

2013-10-01

To develop and test a new algorithm for fast direct Fourier transform (DrFT) reconstruction of MR data on non-Cartesian trajectories composed of lines with equally spaced points. The DrFT, which is normally used as a reference in evaluating the accuracy of other reconstruction methods, can reconstruct images directly from non-Cartesian MR data without interpolation. However, DrFT reconstruction involves substantially intensive computation, which makes the DrFT impractical for clinical routine applications. In this article, the Chirp transform algorithm was introduced to accelerate the DrFT reconstruction of radial and Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI data located on the trajectories that are composed of lines with equally spaced points. The performance of the proposed Chirp transform algorithm-DrFT algorithm was evaluated by using simulation and in vivo MRI data. After implementing the algorithm on a graphics processing unit, the proposed Chirp transform algorithm-DrFT algorithm achieved an acceleration of approximately one order of magnitude, and the speed-up factor was further increased to approximately three orders of magnitude compared with the traditional single-thread DrFT reconstruction. Implementation the Chirp transform algorithm-DrFT algorithm on the graphics processing unit can efficiently calculate the DrFT reconstruction of the radial and PROPELLER MRI data. Copyright © 2012 Wiley Periodicals, Inc.

A fast reconstruction algorithm for fluorescence optical diffusion tomography based on preiteration.

PubMed

Song, Xiaolei; Xiong, Xiaoyun; Bai, Jing

2007-01-01

Fluorescence optical diffusion tomography in the near-infrared (NIR) bandwidth is considered to be one of the most promising ways for noninvasive molecular-based imaging. Many reconstructive approaches to it utilize iterative methods for data inversion. However, they are time-consuming and they are far from meeting the real-time imaging demands. In this work, a fast preiteration algorithm based on the generalized inverse matrix is proposed. This method needs only one step of matrix-vector multiplication online, by pushing the iteration process to be executed offline. In the preiteration process, the second-order iterative format is employed to exponentially accelerate the convergence. Simulations based on an analytical diffusion model show that the distribution of fluorescent yield can be well estimated by this algorithm and the reconstructed speed is remarkably increased.

Application of distance-dependent resolution compensation and post-reconstruction filtering for myocardial SPECT

NASA Astrophysics Data System (ADS)

Hutton, Brian F.; Lau, Yiu H.

1998-06-01

Compensation for distance-dependent resolution can be directly incorporated in maximum likelihood reconstruction. Our objective was to examine the effectiveness of this compensation using either the standard expectation maximization (EM) algorithm or an accelerated algorithm based on use of ordered subsets (OSEM). We also investigated the application of post-reconstruction filtering in combination with resolution compensation. Using the MCAT phantom, projections were simulated for data, including attenuation and distance-dependent resolution. Projection data were reconstructed using conventional EM and OSEM with subset size 2 and 4, with/without 3D compensation for detector response (CDR). Also post-reconstruction filtering (PRF) was performed using a 3D Butterworth filter of order 5 with various cutoff frequencies (0.2-). Image quality and reconstruction accuracy were improved when CDR was included. Image noise was lower with CDR for a given iteration number. PRF with cutoff frequency greater than improved noise with no reduction in recovery coefficient for myocardium but the effect was less when CDR was incorporated in the reconstruction. CDR alone provided better results than use of PRF without CDR. Results suggest that using CDR without PRF, and stopping at a small number of iterations, may provide sufficiently good results for myocardial SPECT. Similar behaviour was demonstrated for OSEM.

An Efficient Framework for Compressed Sensing Reconstruction of Highly Accelerated Dynamic Cardiac MRI

NASA Astrophysics Data System (ADS)

Ting, Samuel T.

The research presented in this work seeks to develop, validate, and deploy practical techniques for improving diagnosis of cardiovascular disease. In the philosophy of biomedical engineering, we seek to identify an existing medical problem having significant societal and economic effects and address this problem using engineering approaches. Cardiovascular disease is the leading cause of mortality in the United States, accounting for more deaths than any other major cause of death in every year since 1900 with the exception of the year 1918. Cardiovascular disease is estimated to account for almost one-third of all deaths in the United States, with more than 2150 deaths each day, or roughly 1 death every 40 seconds. In the past several decades, a growing array of imaging modalities have proven useful in aiding the diagnosis and evaluation of cardiovascular disease, including computed tomography, single photon emission computed tomography, and echocardiography. In particular, cardiac magnetic resonance imaging is an excellent diagnostic tool that can provide within a single exam a high quality evaluation of cardiac function, blood flow, perfusion, viability, and edema without the use of ionizing radiation. The scope of this work focuses on the application of engineering techniques for improving imaging using cardiac magnetic resonance with the goal of improving the utility of this powerful imaging modality. Dynamic cine imaging, or the capturing of movies of a single slice or volume within the heart or great vessel region, is used in nearly every cardiac magnetic resonance imaging exam, and adequate evaluation of cardiac function and morphology for diagnosis and evaluation of cardiovascular disease depends heavily on both the spatial and temporal resolution as well as the image quality of the reconstruction cine images. This work focuses primarily on image reconstruction techniques utilized in cine imaging; however, the techniques discussed are also relevant to other dynamic and static imaging techniques based on cardiac magnetic resonance. Conventional segmented techniques for cardiac cine imaging require breath-holding as well as regular cardiac rhythm, and can be time-consuming to acquire. Inadequate breath-holding or irregular cardiac rhythm can result in completely non-diagnostic images, limiting the utility of these techniques in a significant patient population. Real-time single-shot cardiac cine imaging enables free-breathing acquisition with significantly shortened imaging time and promises to significantly improve the utility of cine imaging for diagnosis and evaluation of cardiovascular disease. However, utility of real-time cine images depends heavily on the successful reconstruction of final cine images from undersampled data. Successful reconstruction of images from more highly undersampled data results directly in images exhibiting finer spatial and temporal resolution provided that image quality is sufficient. This work focuses primarily on the development, validation, and deployment of practical techniques for enabling the reconstruction of real-time cardiac cine images at the spatial and temporal resolutions and image quality needed for diagnostic utility. Particular emphasis is placed on the development of reconstruction approaches resulting in with short computation times that can be used in the clinical environment. Specifically, the use of compressed sensing signal recovery techniques is considered; such techniques show great promise in allowing successful reconstruction of highly undersampled data. The scope of this work concerns two primary topics related to signal recovery using compressed sensing: (1) long reconstruction times of these techniques, and (2) improved sparsity models for signal recovery from more highly undersampled data. Both of these aspects are relevant to the practical application of compressed sensing techniques in the context of improving image reconstruction of real-time cardiac cine images. First, algorithmic and implementational approaches are proposed for reducing the computational time for a compressed sensing reconstruction framework. Specific optimization algorithms based on the fast iterative/shrinkage algorithm (FISTA) are applied in the context of real-time cine image reconstruction to achieve efficient per-iteration computation time. Implementation within a code framework utilizing commercially available graphics processing units (GPUs) allows for practical and efficient implementation directly within the clinical environment. Second, patch-based sparsity models are proposed to enable compressed sensing signal recovery from highly undersampled data. Numerical studies demonstrate that this approach can help improve image quality at higher undersampling ratios, enabling real-time cine imaging at higher acceleration rates. In this work, it is shown that these techniques yield a holistic framework for achieving efficient reconstruction of real-time cine images with spatial and temporal resolution sufficient for use in the clinical environment. A thorough description of these techniques from both a theoretical and practical view is provided - both of which may be of interest to the reader in terms of future work.

Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resolution of Transverse Electron Beam Measurements using Optical Transition Radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ischebeck, Rasmus; Decker, Franz-Josef; Hogan, Mark

2005-06-22

In the plasma wakefield acceleration experiment E-167, optical transition radiation is used to measure the transverse profile of the electron bunches before and after the plasma acceleration. The distribution of the electric field from a single electron does not give a point-like distribution on the detector, but has a certain extension. Additionally, the resolution of the imaging system is affected by aberrations. The transverse profile of the bunch is thus convolved with a point spread function (PSF). Algorithms that deconvolve the image can help to improve the resolution. Imaged test patterns are used to determine the modulation transfer function ofmore » the lens. From this, the PSF can be reconstructed. The Lucy-Richardson algorithm is used to deconvolute this PSF from test images.« less

A Bayesian model for highly accelerated phase-contrast MRI.

PubMed

Rich, Adam; Potter, Lee C; Jin, Ning; Ash, Joshua; Simonetti, Orlando P; Ahmad, Rizwan

2016-08-01

Phase-contrast magnetic resonance imaging is a noninvasive tool to assess cardiovascular disease by quantifying blood flow; however, low data acquisition efficiency limits the spatial and temporal resolutions, real-time application, and extensions to four-dimensional flow imaging in clinical settings. We propose a new data processing approach called Reconstructing Velocity Encoded MRI with Approximate message passing aLgorithms (ReVEAL) that accelerates the acquisition by exploiting data structure unique to phase-contrast magnetic resonance imaging. The proposed approach models physical correlations across space, time, and velocity encodings. The proposed Bayesian approach exploits the relationships in both magnitude and phase among velocity encodings. A fast iterative recovery algorithm is introduced based on message passing. For validation, prospectively undersampled data are processed from a pulsatile flow phantom and five healthy volunteers. The proposed approach is in good agreement, quantified by peak velocity and stroke volume (SV), with reference data for acceleration rates R≤10. For SV, Pearson r≥0.99 for phantom imaging (n = 24) and r≥0.96 for prospectively accelerated in vivo imaging (n = 10) for R≤10. The proposed approach enables accurate quantification of blood flow from highly undersampled data. The technique is extensible to four-dimensional flow imaging, where higher acceleration may be possible due to additional redundancy. Magn Reson Med 76:689-701, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

PubMed

Chiew, Mark; Graedel, Nadine N; Miller, Karla L

2018-07-01

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Considering low-rank, sparse and gas-inflow effects constraints for accelerated pulmonary dynamic hyperpolarized 129Xe MRI

NASA Astrophysics Data System (ADS)

Xiao, Sa; Deng, He; Duan, Caohui; Xie, Junshuai; Zhang, Huiting; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2018-05-01

Dynamic hyperpolarized (HP) 129Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution.

Comparison and analysis of nonlinear algorithms for compressed sensing in MRI.

PubMed

Yu, Yeyang; Hong, Mingjian; Liu, Feng; Wang, Hua; Crozier, Stuart

2010-01-01

Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive; overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI.

Feasibility of through-time spiral generalized autocalibrating partial parallel acquisition for low latency accelerated real-time MRI of speech.

PubMed

Lingala, Sajan Goud; Zhu, Yinghua; Lim, Yongwan; Toutios, Asterios; Ji, Yunhua; Lo, Wei-Ching; Seiberlich, Nicole; Narayanan, Shrikanth; Nayak, Krishna S

2017-12-01

To evaluate the feasibility of through-time spiral generalized autocalibrating partial parallel acquisition (GRAPPA) for low-latency accelerated real-time MRI of speech. Through-time spiral GRAPPA (spiral GRAPPA), a fast linear reconstruction method, is applied to spiral (k-t) data acquired from an eight-channel custom upper-airway coil. Fully sampled data were retrospectively down-sampled to evaluate spiral GRAPPA at undersampling factors R = 2 to 6. Pseudo-golden-angle spiral acquisitions were used for prospective studies. Three subjects were imaged while performing a range of speech tasks that involved rapid articulator movements, including fluent speech and beat-boxing. Spiral GRAPPA was compared with view sharing, and a parallel imaging and compressed sensing (PI-CS) method. Spiral GRAPPA captured spatiotemporal dynamics of vocal tract articulators at undersampling factors ≤4. Spiral GRAPPA at 18 ms/frame and 2.4 mm 2 /pixel outperformed view sharing in depicting rapidly moving articulators. Spiral GRAPPA and PI-CS provided equivalent temporal fidelity. Reconstruction latency per frame was 14 ms for view sharing and 116 ms for spiral GRAPPA, using a single processor. Spiral GRAPPA kept up with the MRI data rate of 18ms/frame with eight processors. PI-CS required 17 minutes to reconstruct 5 seconds of dynamic data. Spiral GRAPPA enabled 4-fold accelerated real-time MRI of speech with a low reconstruction latency. This approach is applicable to wide range of speech RT-MRI experiments that benefit from real-time feedback while visualizing rapid articulator movement. Magn Reson Med 78:2275-2282, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Three-dimensional through-time radial GRAPPA for renal MR angiography.

PubMed

Wright, Katherine L; Lee, Gregory R; Ehses, Philipp; Griswold, Mark A; Gulani, Vikas; Seiberlich, Nicole

2014-10-01

To achieve high temporal and spatial resolution for contrast-enhanced time-resolved MR angiography exams (trMRAs), fast imaging techniques such as non-Cartesian parallel imaging must be used. In this study, the three-dimensional (3D) through-time radial generalized autocalibrating partially parallel acquisition (GRAPPA) method is used to reconstruct highly accelerated stack-of-stars data for time-resolved renal MRAs. Through-time radial GRAPPA has been recently introduced as a method for non-Cartesian GRAPPA weight calibration, and a similar concept can also be used in 3D acquisitions. By combining different sources of calibration information, acquisition time can be reduced. Here, different GRAPPA weight calibration schemes are explored in simulation, and the results are applied to reconstruct undersampled stack-of-stars data. Simulations demonstrate that an accurate and efficient approach to 3D calibration is to combine a small number of central partitions with as many temporal repetitions as exam time permits. These findings were used to reconstruct renal trMRA data with an in-plane acceleration factor as high as 12.6 with respect to the Nyquist sampling criterion, where the lowest root mean squared error value of 16.4% was achieved when using a calibration scheme with 8 partitions, 16 repetitions, and a 4 projection × 8 read point segment size. 3D through-time radial GRAPPA can be used to successfully reconstruct highly accelerated non-Cartesian data. By using in-plane radial undersampling, a trMRA can be acquired with a temporal footprint less than 4s/frame with a spatial resolution of approximately 1.5 mm × 1.5 mm × 3 mm. © 2014 Wiley Periodicals, Inc.

A general Bayesian image reconstruction algorithm with entropy prior: Preliminary application to HST data

NASA Astrophysics Data System (ADS)

Nunez, Jorge; Llacer, Jorge

1993-10-01

This paper describes a general Bayesian iterative algorithm with entropy prior for image reconstruction. It solves the cases of both pure Poisson data and Poisson data with Gaussian readout noise. The algorithm maintains positivity of the solution; it includes case-specific prior information (default map) and flatfield corrections; it removes background and can be accelerated to be faster than the Richardson-Lucy algorithm. In order to determine the hyperparameter that balances the entropy and liklihood terms in the Bayesian approach, we have used a liklihood cross-validation technique. Cross-validation is more robust than other methods because it is less demanding in terms of the knowledge of exact data characteristics and of the point-spread function. We have used the algorithm to reconstruct successfully images obtained in different space-and ground-based imaging situations. It has been possible to recover most of the original intended capabilities of the Hubble Space Telescope (HST) wide field and planetary camera (WFPC) and faint object camera (FOC) from images obtained in their present state. Semireal simulations for the future wide field planetary camera 2 show that even after the repair of the spherical abberration problem, image reconstruction can play a key role in improving the resolution of the cameras, well beyond the design of the Hubble instruments. We also show that ground-based images can be reconstructed successfully with the algorithm. A technique which consists of dividing the CCD observations into two frames, with one-half the exposure time each, emerges as a recommended procedure for the utilization of the described algorithms. We have compared our technique with two commonly used reconstruction algorithms: the Richardson-Lucy and the Cambridge maximum entropy algorithms.

Accelerating Dynamic Magnetic Resonance Imaging (MRI) for Lung Tumor Tracking Based on Low-Rank Decomposition in the Spatial–Temporal Domain: A Feasibility Study Based on Simulation and Preliminary Prospective Undersampled MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarma, Manoj; Department of Radiation Oncology, University of California, Los Angeles, California; Hu, Peng

Purpose: To evaluate a low-rank decomposition method to reconstruct down-sampled k-space data for the purpose of tumor tracking. Methods and Materials: Seven retrospective lung cancer patients were included in the simulation study. The fully-sampled k-space data were first generated from existing 2-dimensional dynamic MR images and then down-sampled by 5 × -20 × before reconstruction using a Cartesian undersampling mask. Two methods, a low-rank decomposition method using combined dynamic MR images (k-t SLR based on sparsity and low-rank penalties) and a total variation (TV) method using individual dynamic MR frames, were used to reconstruct images. The tumor trajectories were derived on the basis ofmore » autosegmentation of the resultant images. To further test its feasibility, k-t SLR was used to reconstruct prospective data of a healthy subject. An undersampled balanced steady-state free precession sequence with the same undersampling mask was used to acquire the imaging data. Results: In the simulation study, higher imaging fidelity and low noise levels were achieved with the k-t SLR compared with TV. At 10 × undersampling, the k-t SLR method resulted in an average normalized mean square error <0.05, as opposed to 0.23 by using the TV reconstruction on individual frames. Less than 6% showed tracking errors >1 mm with 10 × down-sampling using k-t SLR, as opposed to 17% using TV. In the prospective study, k-t SLR substantially reduced reconstruction artifacts and retained anatomic details. Conclusions: Magnetic resonance reconstruction using k-t SLR on highly undersampled dynamic MR imaging data results in high image quality useful for tumor tracking. The k-t SLR was superior to TV by better exploiting the intrinsic anatomic coherence of the same patient. The feasibility of k-t SLR was demonstrated by prospective imaging acquisition and reconstruction.« less

WE-DE-BRA-01: SCIENCE COUNCIL JUNIOR INVESTIGATOR COMPETITION WINNER: Acceleration of a Limited-Angle Intrafraction Verification (LIVE) System Using Adaptive Prior Knowledge Based Image Estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Y; Yin, F; Ren, L

Purpose: To develop an adaptive prior knowledge based image estimation method to reduce the scan angle needed in the LIVE system to reconstruct 4D-CBCT for intrafraction verification. Methods: The LIVE system has been previously proposed to reconstructs 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. This system uses limited-angle beam’s eye view (BEV) MV cine images acquired from the treatment beam together with the orthogonally acquired limited-angle kV projections to reconstruct 4D-CBCT images for target verification during treatment. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to furthermore » reduce the scanning angle needed to reconstruct the CBCT images. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on projections acquired in limited angle (orthogonal 6°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of patient motion.The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the efficacy of this technique with LIVE system. A lung patient was simulated with different scenario, including baseline drifts, amplitude change and phase shift. Limited-angle orthogonal kV and beam’s eye view (BEV) MV projections were generated for each scenario. The CBCT reconstructed by these projections were compared with the ground-truth generated in XCAT.Volume-percentage-difference (VPD) and center-of-mass-shift (COMS) were calculated between the reconstructed and the ground-truth tumors to evaluate the reconstruction accuracy. Results: Using orthogonal-view of 6° kV and BEV- MV projections, the VPD/COMS values were 12.7±4.0%/0.7±0.5 mm, 13.0±5.1%/0.8±0.5 mm, and 11.4±5.4%/0.5±0.3 mm for the three scenarios, respectively. Conclusion: The technique enables LIVE to accurately reconstruct 4D-CBCT images using only orthogonal 6° angle, which greatly improves the efficiency and reduces dose of LIVE for intrafraction verification.« less

Scatter correction, intermediate view estimation and dose characterization in megavoltage cone-beam CT imaging

NASA Astrophysics Data System (ADS)

Sramek, Benjamin Koerner

The ability to deliver conformal dose distributions in radiation therapy through intensity modulation and the potential for tumor dose escalation to improve treatment outcome has necessitated an increase in localization accuracy of inter- and intra-fractional patient geometry. Megavoltage cone-beam CT imaging using the treatment beam and onboard electronic portal imaging device is one option currently being studied for implementation in image-guided radiation therapy. However, routine clinical use is predicated upon continued improvements in image quality and patient dose delivered during acquisition. The formal statement of hypothesis for this investigation was that the conformity of planned to delivered dose distributions in image-guided radiation therapy could be further enhanced through the application of kilovoltage scatter correction and intermediate view estimation techniques to megavoltage cone-beam CT imaging, and that normalized dose measurements could be acquired and inter-compared between multiple imaging geometries. The specific aims of this investigation were to: (1) incorporate the Feldkamp, Davis and Kress filtered backprojection algorithm into a program to reconstruct a voxelized linear attenuation coefficient dataset from a set of acquired megavoltage cone-beam CT projections, (2) characterize the effects on megavoltage cone-beam CT image quality resulting from the application of Intermediate View Interpolation and Intermediate View Reprojection techniques to limited-projection datasets, (3) incorporate the Scatter and Primary Estimation from Collimator Shadows (SPECS) algorithm into megavoltage cone-beam CT image reconstruction and determine the set of SPECS parameters which maximize image quality and quantitative accuracy, and (4) evaluate the normalized axial dose distributions received during megavoltage cone-beam CT image acquisition using radiochromic film and thermoluminescent dosimeter measurements in anthropomorphic pelvic and head and neck phantoms. The conclusions of this investigation were: (1) the implementation of intermediate view estimation techniques to megavoltage cone-beam CT produced improvements in image quality, with the largest impact occurring for smaller numbers of initially-acquired projections, (2) the SPECS scatter correction algorithm could be successfully incorporated into projection data acquired using an electronic portal imaging device during megavoltage cone-beam CT image reconstruction, (3) a large range of SPECS parameters were shown to reduce cupping artifacts as well as improve reconstruction accuracy, with application to anthropomorphic phantom geometries improving the percent difference in reconstructed electron density for soft tissue from -13.6% to -2.0%, and for cortical bone from -9.7% to 1.4%, (4) dose measurements in the anthropomorphic phantoms showed consistent agreement between planar measurements using radiochromic film and point measurements using thermoluminescent dosimeters, and (5) a comparison of normalized dose measurements acquired with radiochromic film to those calculated using multiple treatment planning systems, accelerator-detector combinations, patient geometries and accelerator outputs produced a relatively good agreement.

Frequency domain zero padding for accurate autofocusing based on digital holography

NASA Astrophysics Data System (ADS)

Shin, Jun Geun; Kim, Ju Wan; Eom, Tae Joong; Lee, Byeong Ha

2018-01-01

The numerical refocusing feature of digital holography enables the reconstruction of a well-focused image from a digital hologram captured at an arbitrary out-of-focus plane without the supervision of end users. However, in general, the autofocusing process for getting a highly focused image requires a considerable computational cost. In this study, to reconstruct a better-focused image, we propose the zero padding technique implemented in the frequency domain. Zero padding in the frequency domain enhances the visibility or numerical resolution of the image, which allows one to measure the degree of focus with more accuracy. A coarse-to-fine search algorithm is used to reduce the computing load, and a graphics processing unit (GPU) is employed to accelerate the process. The performance of the proposed scheme is evaluated with simulation and experiment, and the possibility of obtaining a well-refocused image with an enhanced accuracy and speed are presented.

Simultaneous multislice magnetic resonance fingerprinting (SMS-MRF) with direct-spiral slice-GRAPPA (ds-SG) reconstruction.

PubMed

Ye, Huihui; Cauley, Stephen F; Gagoski, Borjan; Bilgic, Berkin; Ma, Dan; Jiang, Yun; Du, Yiping P; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-05-01

To develop a reconstruction method to improve SMS-MRF, in which slice acceleration is used in conjunction with highly undersampled in-plane acceleration to speed up MRF acquisition. In this work two methods are employed to efficiently perform the simultaneous multislice magnetic resonance fingerprinting (SMS-MRF) data acquisition and the direct-spiral slice-GRAPPA (ds-SG) reconstruction. First, the lengthy training data acquisition is shortened by employing the through-time/through-k-space approach, in which similar k-space locations within and across spiral interleaves are grouped and are associated with a single set of kernel. Second, inversion recovery preparation (IR prepped), variable flip angle (FA), and repetition time (TR) are used for the acquisition of the training data, to increase signal variation and to improve the conditioning of the kernel fitting. The grouping of k-space locations enables a large reduction in the number of kernels required, and the IR-prepped training data with variable FA and TR provide improved ds-SG kernels and reconstruction performance. With direct-spiral slice-GRAPPA, tissue parameter maps comparable to that of conventional MRF were obtained at multiband (MB) = 3 acceleration using t-blipped SMS-MRF acquisition with 32-channel head coil at 3 Tesla (T). The proposed reconstruction scheme allows MB = 3 accelerated SMS-MRF imaging with high-quality T 1 , T 2 , and off-resonance maps, and can be used to significantly shorten MRF acquisition and aid in its adoption in neuro-scientific and clinical settings. Magn Reson Med 77:1966-1974, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bai, T; UT Southwestern Medical Center, Dallas, TX; Yan, H

2014-06-15

Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm inmore » a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application. A high zresolution is preferred to stabilize statistical iterative reconstruction. This work was supported in part by NIH(1R01CA154747-01), NSFC((No. 61172163), Research Fund for the Doctoral Program of Higher Education of China (No. 20110201110011), China Scholarship Council.« less

Self-Calibrating Wave-Encoded Variable-Density Single-Shot Fast Spin Echo Imaging.

PubMed

Chen, Feiyu; Taviani, Valentina; Tamir, Jonathan I; Cheng, Joseph Y; Zhang, Tao; Song, Qiong; Hargreaves, Brian A; Pauly, John M; Vasanawala, Shreyas S

2018-04-01

It is highly desirable in clinical abdominal MR scans to accelerate single-shot fast spin echo (SSFSE) imaging and reduce blurring due to T 2 decay and partial-Fourier acquisition. To develop and investigate the clinical feasibility of wave-encoded variable-density SSFSE imaging for improved image quality and scan time reduction. Prospective controlled clinical trial. With Institutional Review Board approval and informed consent, the proposed method was assessed on 20 consecutive adult patients (10 male, 10 female, range, 24-84 years). A wave-encoded variable-density SSFSE sequence was developed for clinical 3.0T abdominal scans to enable high acceleration (3.5×) with full-Fourier acquisitions by: 1) introducing wave encoding with self-refocusing gradient waveforms to improve acquisition efficiency; 2) developing self-calibrated estimation of wave-encoding point-spread function and coil sensitivity to improve motion robustness; and 3) incorporating a parallel imaging and compressed sensing reconstruction to reconstruct highly accelerated datasets. Image quality was compared pairwise with standard Cartesian acquisition independently and blindly by two radiologists on a scale from -2 to 2 for noise, contrast, confidence, sharpness, and artifacts. The average ratio of scan time between these two approaches was also compared. A Wilcoxon signed-rank tests with a P value under 0.05 considered statistically significant. Wave-encoded variable-density SSFSE significantly reduced the perceived noise level and improved the sharpness of the abdominal wall and the kidneys compared with standard acquisition (mean scores 0.8, 1.2, and 0.8, respectively, P < 0.003). No significant difference was observed in relation to other features (P = 0.11). An average of 21% decrease in scan time was achieved using the proposed method. Wave-encoded variable-density sampling SSFSE achieves improved image quality with clinically relevant echo time and reduced scan time, thus providing a fast and robust approach for clinical SSFSE imaging. 1 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2018;47:954-966. © 2017 International Society for Magnetic Resonance in Medicine.

A fast CT reconstruction scheme for a general multi-core PC.

PubMed

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.

A Fast CT Reconstruction Scheme for a General Multi-Core PC

PubMed Central

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors. PMID:18256731

Region-of-interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy

PubMed Central

Cho, Seungryong; Pearson, Erik; Pelizzari, Charles A.; Pan, Xiaochuan

2009-01-01

Imaging plays a vital role in radiation therapy and with recent advances in technology considerable emphasis has been placed on cone-beam CT (CBCT). Attaching a kV x-ray source and a flat panel detector directly to the linear accelerator gantry has enabled progress in target localization techniques, which can include daily CBCT setup scans for some treatments. However, with an increasing number of CT scans there is also an increasing concern for patient exposure. An intensity-weighted region-of-interest (IWROI) technique, which has the potential to greatly reduce CBCT dose, in conjunction with the chord-based backprojection-filtration (BPF) reconstruction algorithm, has been developed and its feasibility in clinical use is demonstrated in this article. A nonuniform filter is placed in the x-ray beam to create regions of two different beam intensities. In this manner, regions outside the target area can be given a reduced dose but still visualized with a lower contrast to noise ratio. Image artifacts due to transverse data truncation, which would have occurred in conventional reconstruction algorithms, are avoided and image noise levels of the low- and high-intensity regions are well controlled by use of the chord-based BPF reconstruction algorithm. The proposed IWROI technique can play an important role in image-guided radiation therapy. PMID:19472624

Segmented Separable Footprint Projector for Digital Breast Tomosynthesis and Its application for Subpixel Reconstruction

PubMed Central

Zheng, Jiabei; Fessler, Jeffrey A; Chan, Heang-Ping

2017-01-01

Purpose Digital forward and back projectors play a significant role in iterative image reconstruction. The accuracy of the projector affects the quality of the reconstructed images. Digital breast tomosynthesis (DBT) often uses the ray-tracing (RT) projector that ignores finite detector element size. This paper proposes a modified version of the separable footprint (SF) projector, called the segmented separable footprint (SG) projector, that calculates efficiently the Radon transform mean value over each detector element. The SG projector is specifically designed for DBT reconstruction because of the large height-to-width ratio of the voxels generally used in DBT. This study evaluates the effectiveness of the SG projector in reducing projection error and improving DBT reconstruction quality. Methods We quantitatively compared the projection error of the RT and the SG projector at different locations and their performance in regular and subpixel DBT reconstruction. Subpixel reconstructions used finer voxels in the imaged volume than the detector pixel size. Subpixel reconstruction with RT projector uses interpolated projection views as input to provide adequate coverage of the finer voxel grid with the traced rays. Subpixel reconstruction with the SG projector, however, uses the measured projection views without interpolation. We simulated DBT projections of a test phantom using CatSim (GE Global Research, Niskayuna, NY) under idealized imaging conditions without noise and blur, to analyze the effects of the projectors and subpixel reconstruction without other image degrading factors. The phantom contained an array of horizontal and vertical line pair patterns (1 to 9.5 line pairs/mm) and pairs of closely spaced spheres (diameters 0.053 to 0.5 mm) embedded at the mid-plane of a 5-cm-thick breast-tissue-equivalent uniform volume. The images were reconstructed with regular simultaneous algebraic reconstruction technique (SART) and subpixel SART using different projectors. The resolution and contrast of the test objects in the reconstructed images and the computation times were compared under different reconstruction conditions. Results The SG projector reduced the projector error by 1 to 2 orders of magnitude at most locations. In the worst case, the SG projector still reduced the projection error by about 50%. In the DBT reconstructed slices parallel to the detector plane, the SG projector not only increased the contrast of the line pairs and spheres, but also produced more smooth and continuous reconstructed images whereas the discrete and sparse nature of the RT projector caused artifacts appearing as patterned noise. For subpixel reconstruction, the SG projector significantly increased object contrast and computation speed, especially for high subpixel ratios, compared with the RT projector implemented with accelerated Siddon’s algorithm. The difference in the depth resolution among the projectors is negligible under the conditions studied. Our results also demonstrated that subpixel reconstruction can improve the spatial resolution of the reconstructed images, and can exceed the Nyquist limit of the detector under some conditions. Conclusions The SG projector was more accurate and faster than the RT projector. The SG projector also substantially reduced computation time and improved the image quality for the tomosynthesized images with and without subpixel reconstruction. PMID:28058719

Fast optical transillumination tomography with large-size projection acquisition.

PubMed

Huang, Hsuan-Ming; Xia, Jinjun; Haidekker, Mark A

2008-10-01

Techniques such as optical coherence tomography and diffuse optical tomography have been shown to effectively image highly scattering samples such as tissue. An additional modality has received much less attention: Optical transillumination (OT) tomography, a modality that promises very high acquisition speed for volumetric scans. With the motivation to image tissue-engineered blood vessels for possible biomechanical testing, we have developed a fast OT device using a collimated, noncoherent beam with a large diameter together with a large-size CMOS camera that has the ability to acquire 3D projections in a single revolution of the sample. In addition, we used accelerated iterative reconstruction techniques to improve image reconstruction speed, while at the same time obtaining better image quality than through filtered backprojection. The device was tested using ink-filled polytetrafluorethylene tubes to determine geometric reconstruction accuracy and recovery of absorbance. Even in the presence of minor refractive index mismatch, the weighted error of the measured radius was <5% in all cases, and a high linear correlation of ink absorbance determined with a photospectrometer of R(2) = 0.99 was found, although the OT device systematically underestimated absorbance. Reconstruction time was improved from several hours (standard arithmetic reconstruction) to 90 s per slice with our optimized algorithm. Composed of only a light source, two spatial filters, a sample bath, and a CMOS camera, this device was extremely simple and cost-efficient to build.

Is Remnant Preservation Truly Beneficial to Anterior Cruciate Ligament Reconstruction Healing? Clinical and Magnetic Resonance Imaging Evaluations of Remnant-Preserved Reconstruction.

PubMed

Naraoka, Takuya; Kimura, Yuka; Tsuda, Eiichi; Yamamoto, Yuji; Ishibashi, Yasuyuki

2017-04-01

Remnant-preserved anterior cruciate ligament (ACL) reconstruction was introduced to improve clinical outcomes and biological healing. However, the effects of remnant preservation and the influence of the delay from injury until reconstruction on the outcomes of this technique are still uncertain. Purpose/Hypothesis: The purposes of this study were to evaluate whether remnant preservation improved the clinical outcomes and graft incorporation of ACL reconstruction and to examine the influence of the delay between ACL injury and reconstruction on the usefulness of remnant preservation. We hypothesized that remnant preservation improves clinical results and accelerates graft incorporation and that its effect is dependent on the delay between ACL injury and reconstruction. Cohort study; Level of evidence, 2. A total of 151 consecutive patients who underwent double-bundle ACL reconstruction using a semitendinosus graft were enrolled in this study: 74 knees underwent ACL reconstruction without a remnant (or the remnant was <25% of the intra-articular portion of the graft; NR group), while 77 knees underwent ACL reconstruction with remnant preservation (RP group). These were divided into 4 subgroups based on the time from injury to surgery: phase 1 was <3 weeks (n = 24), phase 2 was 3 to less than 8 weeks (n = 70), phase 3 was 8 to 20 weeks (n = 32), and phase 4 was >20 weeks (n = 25). Clinical measurements, including KT-1000 arthrometer side-to-side anterior tibial translation measurements, were assessed at 3, 6, 12, and 24 months after reconstruction. Magnetic resonance imaging evaluations of graft maturation and graft-tunnel integration of the anteromedial and posterolateral bundles were assessed at 3, 6, and 12 months after reconstruction. There was no difference in side-to-side anterior tibial translation between the NR and RP groups. There was also no difference in graft maturation between the 2 groups. Furthermore, the time from ACL injury until reconstruction did not affect graft maturation, except in the case of very long delays before reconstruction (phase 4). Graft-tunnel integration was significantly increased in both groups in a time-dependent manner. However, there was no difference between the NR and RP groups. Remnant preservation did not improve knee stability at 2 years after ACL reconstruction. Furthermore, remnant preservation did not accelerate graft incorporation, especially during the acute and subacute injury phases.

Direct and accelerated parameter mapping using the unscented Kalman filter.

PubMed

Zhao, Li; Feng, Xue; Meyer, Craig H

2016-05-01

To accelerate parameter mapping using a new paradigm that combines image reconstruction and model regression as a parameter state-tracking problem. In T2 mapping, the T2 map is first encoded in parameter space by multi-TE measurements and then encoded by Fourier transformation with readout/phase encoding gradients. Using a state transition function and a measurement function, the unscented Kalman filter can describe T2 mapping as a dynamic system and directly estimate the T2 map from the k-space data. The proposed method was validated with a numerical brain phantom and volunteer experiments with a multiple-contrast spin echo sequence. Its performance was compared with a conjugate-gradient nonlinear inversion method at undersampling factors of 2 to 8. An accelerated pulse sequence was developed based on this method to achieve prospective undersampling. Compared with the nonlinear inversion reconstruction, the proposed method had higher precision, improved structural similarity and reduced normalized root mean squared error, with acceleration factors up to 8 in numerical phantom and volunteer studies. This work describes a new perspective on parameter mapping by state tracking. The unscented Kalman filter provides a highly accelerated and efficient paradigm for T2 mapping. © 2015 Wiley Periodicals, Inc.

GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration.

PubMed

Sharp, G C; Kandasamy, N; Singh, H; Folkert, M

2007-10-07

This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup--up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.

Single-Shot MR Spectroscopic Imaging with Partial Parallel Imaging

PubMed Central

Posse, Stefan; Otazo, Ricardo; Tsai, Shang-Yueh; Yoshimoto, Akio Ernesto; Lin, Fa-Hsuan

2010-01-01

An MR spectroscopic imaging (MRSI) pulse sequence based on Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) is introduced that measures 2-dimensional metabolite maps in a single excitation. Echo-planar spatial-spectral encoding was combined with interleaved phase encoding and parallel imaging using SENSE to reconstruct absorption mode spectra. The symmetrical k-space trajectory compensates phase errors due to convolution of spatial and spectral encoding. Single-shot MRSI at short TE was evaluated in phantoms and in vivo on a 3 T whole body scanner equipped with 12-channel array coil. Four-step interleaved phase encoding and 4-fold SENSE acceleration were used to encode a 16×16 spatial matrix with 390 Hz spectral width. Comparison with conventional PEPSI and PEPSI with 4-fold SENSE acceleration demonstrated comparable sensitivity per unit time when taking into account g-factor related noise increases and differences in sampling efficiency. LCModel fitting enabled quantification of Inositol, Choline, Creatine and NAA in vivo with concentration values in the ranges measured with conventional PEPSI and SENSE-accelerated PEPSI. Cramer-Rao lower bounds were comparable to those obtained with conventional SENSE-accelerated PEPSI at the same voxel size and measurement time. This single-shot MRSI method is therefore suitable for applications that require high temporal resolution to monitor temporal dynamics or to reduce sensitivity to tissue movement. PMID:19097245

SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, S; Hoffman, J; McNitt-Gray, M

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with amore » quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low-dose helical CT, in particular as part of our ongoing development of an acquisition/reconstruction pipeline for generating images under a wide range of conditions. Our algorithm will be made available open-source as “FreeCT-ICD”. NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less

Ultrasound-directed robotic system for thermal ablation of liver tumors: a preliminary report

NASA Astrophysics Data System (ADS)

Zheng, Jian; Tian, Jie; Dai, Yakang; Zhang, Xing; Dong, Di; Xu, Min

2010-03-01

Thermal ablation has been proved safe and effective as the treatment for liver tumors that are not suitable for resection. Currently, manually performed thermal ablation is greatly dependent on the surgeon's acupuncture manipulation against hand tremor. Besides that, inaccurate or inappropriate placement of the applicator will also directly decrease the final treatment effect. In order to reduce the influence of hand tremor, and provide an accurate and appropriate guidance for a better treatment, we develop an ultrasound-directed robotic system for thermal ablation of liver tumors. In this paper, we will give a brief preliminary report of our system. Especially, three innovative techniques are proposed to solve the critical problems in our system: accurate ultrasound calibration when met with artifacts, realtime reconstruction with visualization using Graphic Processing Unit (GPU) acceleration and 2D-3D ultrasound image registration. To reduce the error of point extraction with artifacts, we propose a novel point extraction method by minimizing an error function which is defined based on the geometric property of our N-fiducial phantom. Then realtime reconstruction with visualization using GPU acceleration is provided for fast 3D ultrasound volume acquisition with dynamic display of reconstruction progress. After that, coarse 2D-3D ultrasound image registration is performed based on landmark points correspondences, followed by accurate 2D-3D ultrasound image registration based on Euclidean distance transform (EDT). The effectiveness of our proposed techniques is demonstrated in phantom experiments.

GPU-Accelerated Forward and Back-Projections with Spatially Varying Kernels for 3D DIRECT TOF PET Reconstruction.

PubMed

Ha, S; Matej, S; Ispiryan, M; Mueller, K

2013-02-01

We describe a GPU-accelerated framework that efficiently models spatially (shift) variant system response kernels and performs forward- and back-projection operations with these kernels for the DIRECT (Direct Image Reconstruction for TOF) iterative reconstruction approach. Inherent challenges arise from the poor memory cache performance at non-axis aligned TOF directions. Focusing on the GPU memory access patterns, we utilize different kinds of GPU memory according to these patterns in order to maximize the memory cache performance. We also exploit the GPU instruction-level parallelism to efficiently hide long latencies from the memory operations. Our experiments indicate that our GPU implementation of the projection operators has slightly faster or approximately comparable time performance than FFT-based approaches using state-of-the-art FFTW routines. However, most importantly, our GPU framework can also efficiently handle any generic system response kernels, such as spatially symmetric and shift-variant as well as spatially asymmetric and shift-variant, both of which an FFT-based approach cannot cope with.

GPU-Accelerated Forward and Back-Projections With Spatially Varying Kernels for 3D DIRECT TOF PET Reconstruction

NASA Astrophysics Data System (ADS)

Ha, S.; Matej, S.; Ispiryan, M.; Mueller, K.

2013-02-01

We describe a GPU-accelerated framework that efficiently models spatially (shift) variant system response kernels and performs forward- and back-projection operations with these kernels for the DIRECT (Direct Image Reconstruction for TOF) iterative reconstruction approach. Inherent challenges arise from the poor memory cache performance at non-axis aligned TOF directions. Focusing on the GPU memory access patterns, we utilize different kinds of GPU memory according to these patterns in order to maximize the memory cache performance. We also exploit the GPU instruction-level parallelism to efficiently hide long latencies from the memory operations. Our experiments indicate that our GPU implementation of the projection operators has slightly faster or approximately comparable time performance than FFT-based approaches using state-of-the-art FFTW routines. However, most importantly, our GPU framework can also efficiently handle any generic system response kernels, such as spatially symmetric and shift-variant as well as spatially asymmetric and shift-variant, both of which an FFT-based approach cannot cope with.

Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

PubMed

Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A

2015-02-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms.

Fast Parallel MR Image Reconstruction via B1-based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA)

PubMed Central

Noll, Douglas C.; Fessler, Jeffrey A.

2014-01-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms. PMID:25330484

Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

NASA Astrophysics Data System (ADS)

Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

2016-02-01

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla.

PubMed

Ardekani, Siamak; Selva, Luis; Sayre, James; Sinha, Usha

2006-11-01

Single-shot echo-planar based diffusion tensor imaging is prone to geometric and intensity distortions. Parallel imaging is a means of reducing these distortions while preserving spatial resolution. A quantitative comparison at 3 T of parallel imaging for diffusion tensor images (DTI) using k-space (generalized auto-calibrating partially parallel acquisitions; GRAPPA) and image domain (sensitivity encoding; SENSE) reconstructions at different acceleration factors, R, is reported here. Images were evaluated using 8 human subjects with repeated scans for 2 subjects to estimate reproducibility. Mutual information (MI) was used to assess the global changes in geometric distortions. The effects of parallel imaging techniques on random noise and reconstruction artifacts were evaluated by placing 26 regions of interest and computing the standard deviation of apparent diffusion coefficient and fractional anisotropy along with the error of fitting the data to the diffusion model (residual error). The larger positive values in mutual information index with increasing R values confirmed the anticipated decrease in distortions. Further, the MI index of GRAPPA sequences for a given R factor was larger than the corresponding mSENSE images. The residual error was lowest in the images acquired without parallel imaging and among the parallel reconstruction methods, the R = 2 acquisitions had the least error. The standard deviation, accuracy, and reproducibility of the apparent diffusion coefficient and fractional anisotropy in homogenous tissue regions showed that GRAPPA acquired with R = 2 had the least amount of systematic and random noise and of these, significant differences with mSENSE, R = 2 were found only for the fractional anisotropy index. Evaluation of the current implementation of parallel reconstruction algorithms identified GRAPPA acquired with R = 2 as optimal for diffusion tensor imaging.

Recent Advances in X-ray Cone-beam Computed Laminography.

PubMed

O'Brien, Neil S; Boardman, Richard P; Sinclair, Ian; Blumensath, Thomas

2016-10-06

X-ray computed tomography is an established volume imaging technique used routinely in medical diagnosis, industrial non-destructive testing, and a wide range of scientific fields. Traditionally, computed tomography uses scanning geometries with a single axis of rotation together with reconstruction algorithms specifically designed for this setup. Recently there has however been increasing interest in more complex scanning geometries. These include so called X-ray computed laminography systems capable of imaging specimens with large lateral dimensions or large aspect ratios, neither of which are well suited to conventional CT scanning procedures. Developments throughout this field have thus been rapid, including the introduction of novel system trajectories, the application and refinement of various reconstruction methods, and the use of recently developed computational hardware and software techniques to accelerate reconstruction times. Here we examine the advances made in the last several years and consider their impact on the state of the art.

Real-time digital holographic microscopy using the graphic processing unit.

PubMed

Shimobaba, Tomoyoshi; Sato, Yoshikuni; Miura, Junya; Takenouchi, Mai; Ito, Tomoyoshi

2008-08-04

Digital holographic microscopy (DHM) is a well-known powerful method allowing both the amplitude and phase of a specimen to be simultaneously observed. In order to obtain a reconstructed image from a hologram, numerous calculations for the Fresnel diffraction are required. The Fresnel diffraction can be accelerated by the FFT (Fast Fourier Transform) algorithm. However, real-time reconstruction from a hologram is difficult even if we use a recent central processing unit (CPU) to calculate the Fresnel diffraction by the FFT algorithm. In this paper, we describe a real-time DHM system using a graphic processing unit (GPU) with many stream processors, which allows use as a highly parallel processor. The computational speed of the Fresnel diffraction using the GPU is faster than that of recent CPUs. The real-time DHM system can obtain reconstructed images from holograms whose size is 512 x 512 grids in 24 frames per second.

Highly-accelerated quantitative 2D and 3D localized spectroscopy with linear algebraic modeling (SLAM) and sensitivity encoding

NASA Astrophysics Data System (ADS)

Zhang, Yi; Gabr, Refaat E.; Zhou, Jinyuan; Weiss, Robert G.; Bottomley, Paul A.

2013-12-01

Noninvasive magnetic resonance spectroscopy (MRS) with chemical shift imaging (CSI) provides valuable metabolic information for research and clinical studies, but is often limited by long scan times. Recently, spectroscopy with linear algebraic modeling (SLAM) was shown to provide compartment-averaged spectra resolved in one spatial dimension with many-fold reductions in scan-time. This was achieved using a small subset of the CSI phase-encoding steps from central image k-space that maximized the signal-to-noise ratio. Here, SLAM is extended to two- and three-dimensions (2D, 3D). In addition, SLAM is combined with sensitivity-encoded (SENSE) parallel imaging techniques, enabling the replacement of even more CSI phase-encoding steps to further accelerate scan-speed. A modified SLAM reconstruction algorithm is introduced that significantly reduces the effects of signal nonuniformity within compartments. Finally, main-field inhomogeneity corrections are provided, analogous to CSI. These methods are all tested on brain proton MRS data from a total of 24 patients with brain tumors, and in a human cardiac phosphorus 3D SLAM study at 3T. Acceleration factors of up to 120-fold versus CSI are demonstrated, including speed-up factors of 5-fold relative to already-accelerated SENSE CSI. Brain metabolites are quantified in SLAM and SENSE SLAM spectra and found to be indistinguishable from CSI measures from the same compartments. The modified reconstruction algorithm demonstrated immunity to maladjusted segmentation and errors from signal heterogeneity in brain data. In conclusion, SLAM demonstrates the potential to supplant CSI in studies requiring compartment-average spectra or large volume coverage, by dramatically reducing scan-time while providing essentially the same quantitative results.

An analytical reconstruction model of the spread-out Bragg peak using laser-accelerated proton beams.

PubMed

Tao, Li; Zhu, Kun; Zhu, Jungao; Xu, Xiaohan; Lin, Chen; Ma, Wenjun; Lu, Haiyang; Zhao, Yanying; Lu, Yuanrong; Chen, Jia-Er; Yan, Xueqing

2017-07-07

With the development of laser technology, laser-driven proton acceleration provides a new method for proton tumor therapy. However, it has not been applied in practice because of the wide and decreasing energy spectrum of laser-accelerated proton beams. In this paper, we propose an analytical model to reconstruct the spread-out Bragg peak (SOBP) using laser-accelerated proton beams. Firstly, we present a modified weighting formula for protons of different energies. Secondly, a theoretical model for the reconstruction of SOBPs with laser-accelerated proton beams has been built. It can quickly calculate the number of laser shots needed for each energy interval of the laser-accelerated protons. Finally, we show the 2D reconstruction results of SOBPs for laser-accelerated proton beams and the ideal situation. The final results show that our analytical model can give an SOBP reconstruction scheme that can be used for actual tumor therapy.

SU-G-JeP1-15: Sliding Window Prior Data Assisted Compressed Sensing for MRI Lung Tumor Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yip, E; Wachowicz, K; Rathee, S

Purpose: Prior Data Assisted Compressed Sensing (PDACS) is a partial k-space acquisition and reconstruction method for mobile tumour (i.e. lung) tracking using on-line MRI in radiotherapy. PDACS partially relies on prior data acquired at the beginning of dynamic scans, and is therefore susceptible to artifacts in longer duration scan due to slow drifts in MR signal. A novel sliding window strategy is presented to mitigate this effect. Methods: MRI acceleration is simulated by retrospective removal of data from the fully sampled sets. Six lung cancer patients were scanned (clinical 3T MRI) using a balanced steady state free precession (bSSFP) sequencemore » for 3 minutes at approximately 4 frames per second, for a total of 650 dynamics. PDACS acceleration is achieved by undersampling of k-space in a single pseudo-random pattern. Reconstruction iteratively minimizes the total variations while constraining the images to satisfy both the currently acquired data and the prior data in missing k-space. Our novel sliding window technique (SW-PDACS), uses a series of distinct pseudo-random under-sampling patterns of partial k-space – with the prior data drawn from a sliding window of the most recent data available. Under-sampled data, simulating 2 – 5x acceleration are reconstructed using PDACS and SW-PDACS. Three quantitative metrics: artifact power, centroid error and Dice’s coefficient are computed for comparison. Results: Quantitively metric values from all 6 patients are averaged in 3 bins, each containing approximately one minute of dynamic data. For the first minute bin, PDACS and SW-PDACS give comparable results. Progressive decline in image quality metrics in bins 2 and 3 are observed for PDACS. No decline in image quality is observed for SW-PDACS. Conclusion: The novel approach presented (SW-PDACS) is a more robust for accelerating longer duration (>1 minute) dynamic MRI scans for tracking lung tumour motion using on-line MRI in radiotherapy. B.G. Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization).« less

Development of a chest digital tomosynthesis R/F system and implementation of low-dose GPU-accelerated compressed sensing (CS) image reconstruction.

PubMed

Choi, Sunghoon; Lee, Haenghwa; Lee, Donghoon; Choi, Seungyeon; Lee, Chang-Lae; Kwon, Woocheol; Shin, Jungwook; Seo, Chang-Woo; Kim, Hee-Joung

2018-05-01

This work describes the hardware and software developments of a prototype chest digital tomosynthesis (CDT) R/F system. The purpose of this study was to validate the developed system for its possible clinical application on low-dose chest tomosynthesis imaging. The prototype CDT R/F system was operated by carefully controlling the electromechanical subsystems through a synchronized interface. Once a command signal was delivered by the user, a tomosynthesis sweep started to acquire 81 projection views (PVs) in a limited angular range of ±20°. Among the full projection dataset of 81 images, several sets of 21 (quarter view) and 41 (half view) images with equally spaced angle steps were selected to represent a sparse view condition. GPU-accelerated and total-variation (TV) regularization strategy-based compressed sensing (CS) image reconstruction was implemented. The imaged objects were a flat-field using a copper filter to measure the noise power spectrum (NPS), a Catphan ® CTP682 quality assurance (QA) phantom to measure a task-based modulation transfer function (MTF T ask ) of three different cylinders' edge, and an anthropomorphic chest phantom with inserted lung nodules. The authors also verified the accelerated computing power over CPU programming by checking the elapsed time required for the CS method. The resultant absorbed and effective doses that were delivered to the chest phantom from two-view digital radiographic projections, helical computed tomography (CT), and the prototype CDT system were compared. The prototype CDT system was successfully operated, showing little geometric error with fast rise and fall times of R/F x-ray pulse less than 2 and 10 ms, respectively. The in-plane NPS presented essential symmetric patterns as predicted by the central slice theorem. The NPS images from 21 PVs were provided quite different pattern against 41 and 81 PVs due to aliased noise. The voxel variance values which summed all NPS intensities were inversely proportional to the number of PVs, and the CS method gave much lower voxel variance by the factors of 3.97-6.43 and 2.28-3.36 compared to filtered backprojection (FBP) and 20 iterations of simultaneous algebraic reconstruction technique (SART). The spatial frequencies of the f 50 at which the MTF T ask reduced to 50% were 1.50, 1.55, and 1.67 cycles/mm for FBP, SART, and CS methods, respectively, in the case of Bone 20% cylinder using 41 views. A variety of ranges of TV reconstruction parameters were implemented during the CS method and we could observe that the NPS and MTF T ask preserved best when the regularization and TV smoothing parameters α and τ were in a range of 0.001-0.1. For the chest phantom data, the signal difference to noise ratios (SDNRs) were higher in the proposed CS scheme images than in the FBP and SART, showing the enhanced rate of 1.05-1.43 for half view imaging. The total averaged reconstruction time during 20 iterations of the CS scheme was 124.68 s, which could match-up a clinically feasible time (<3 min). This computing time represented an enhanced speed 386 times greater than CPU programming. The total amounts of estimated effective doses were 0.12, 0.53 (half view), and 2.56 mSv for two-view radiographs, the prototype CDT system, and helical CT, respectively, showing 4.49 times higher than conventional radiography and 4.83 times lower than a CT exam, respectively. The current work describes the development and performance assessment of both hardware and software for tomosynthesis applications. The authors observed reasonable outcomes by showing a potential for low-dose application in CDT imaging using GPU acceleration. © 2018 American Association of Physicists in Medicine.

Conductivity map from scanning tunneling potentiometry.

PubMed

Zhang, Hao; Li, Xianqi; Chen, Yunmei; Durand, Corentin; Li, An-Ping; Zhang, X-G

2016-08-01

We present a novel method for extracting two-dimensional (2D) conductivity profiles from large electrochemical potential datasets acquired by scanning tunneling potentiometry of a 2D conductor. The method consists of a data preprocessing procedure to reduce/eliminate noise and a numerical conductivity reconstruction. The preprocessing procedure employs an inverse consistent image registration method to align the forward and backward scans of the same line for each image line followed by a total variation (TV) based image restoration method to obtain a (nearly) noise-free potential from the aligned scans. The preprocessed potential is then used for numerical conductivity reconstruction, based on a TV model solved by accelerated alternating direction method of multiplier. The method is demonstrated on a measurement of the grain boundary of a monolayer graphene, yielding a nearly 10:1 ratio for the grain boundary resistivity over bulk resistivity.

A low-complexity 2-point step size gradient projection method with selective function evaluations for smoothed total variation based CBCT reconstructions

NASA Astrophysics Data System (ADS)

Song, Bongyong; Park, Justin C.; Song, William Y.

2014-11-01

The Barzilai-Borwein (BB) 2-point step size gradient method is receiving attention for accelerating Total Variation (TV) based CBCT reconstructions. In order to become truly viable for clinical applications, however, its convergence property needs to be properly addressed. We propose a novel fast converging gradient projection BB method that requires ‘at most one function evaluation’ in each iterative step. This Selective Function Evaluation method, referred to as GPBB-SFE in this paper, exhibits the desired convergence property when it is combined with a ‘smoothed TV’ or any other differentiable prior. This way, the proposed GPBB-SFE algorithm offers fast and guaranteed convergence to the desired 3DCBCT image with minimal computational complexity. We first applied this algorithm to a Shepp-Logan numerical phantom. We then applied to a CatPhan 600 physical phantom (The Phantom Laboratory, Salem, NY) and a clinically-treated head-and-neck patient, both acquired from the TrueBeam™ system (Varian Medical Systems, Palo Alto, CA). Furthermore, we accelerated the reconstruction by implementing the algorithm on NVIDIA GTX 480 GPU card. We first compared GPBB-SFE with three recently proposed BB-based CBCT reconstruction methods available in the literature using Shepp-Logan numerical phantom with 40 projections. It is found that GPBB-SFE shows either faster convergence speed/time or superior convergence property compared to existing BB-based algorithms. With the CatPhan 600 physical phantom, the GPBB-SFE algorithm requires only 3 function evaluations in 30 iterations and reconstructs the standard, 364-projection FDK reconstruction quality image using only 60 projections. We then applied the algorithm to a clinically-treated head-and-neck patient. It was observed that the GPBB-SFE algorithm requires only 18 function evaluations in 30 iterations. Compared with the FDK algorithm with 364 projections, the GPBB-SFE algorithm produces visibly equivalent quality CBCT image for the head-and-neck patient with only 180 projections, in 131.7 s, further supporting its clinical applicability.

A low-complexity 2-point step size gradient projection method with selective function evaluations for smoothed total variation based CBCT reconstructions.

PubMed

Song, Bongyong; Park, Justin C; Song, William Y

2014-11-07

The Barzilai-Borwein (BB) 2-point step size gradient method is receiving attention for accelerating Total Variation (TV) based CBCT reconstructions. In order to become truly viable for clinical applications, however, its convergence property needs to be properly addressed. We propose a novel fast converging gradient projection BB method that requires 'at most one function evaluation' in each iterative step. This Selective Function Evaluation method, referred to as GPBB-SFE in this paper, exhibits the desired convergence property when it is combined with a 'smoothed TV' or any other differentiable prior. This way, the proposed GPBB-SFE algorithm offers fast and guaranteed convergence to the desired 3DCBCT image with minimal computational complexity. We first applied this algorithm to a Shepp-Logan numerical phantom. We then applied to a CatPhan 600 physical phantom (The Phantom Laboratory, Salem, NY) and a clinically-treated head-and-neck patient, both acquired from the TrueBeam™ system (Varian Medical Systems, Palo Alto, CA). Furthermore, we accelerated the reconstruction by implementing the algorithm on NVIDIA GTX 480 GPU card. We first compared GPBB-SFE with three recently proposed BB-based CBCT reconstruction methods available in the literature using Shepp-Logan numerical phantom with 40 projections. It is found that GPBB-SFE shows either faster convergence speed/time or superior convergence property compared to existing BB-based algorithms. With the CatPhan 600 physical phantom, the GPBB-SFE algorithm requires only 3 function evaluations in 30 iterations and reconstructs the standard, 364-projection FDK reconstruction quality image using only 60 projections. We then applied the algorithm to a clinically-treated head-and-neck patient. It was observed that the GPBB-SFE algorithm requires only 18 function evaluations in 30 iterations. Compared with the FDK algorithm with 364 projections, the GPBB-SFE algorithm produces visibly equivalent quality CBCT image for the head-and-neck patient with only 180 projections, in 131.7 s, further supporting its clinical applicability.

Evaluation of respiration-correlated digital tomosynthesis in lung.

PubMed

Santoro, Joseph; Kriminski, Sergey; Lovelock, D Michael; Rosenzweig, Kenneth; Mostafavi, Hassan; Amols, Howard I; Mageras, Gig S

2010-03-01

Digital tomosynthesis (DTS) with a linear accelerator-mounted imaging system provides a means of reconstructing tomographic images from radiographic projections over a limited gantry arc, thus requiring only a few seconds to acquire. Its application in the thorax, however, often results in blurred images from respiration-induced motion. This work evaluates the feasibility of respiration-correlated (RC) DTS for soft-tissue visualization and patient positioning. Image data acquired with a gantry-mounted kilovoltage imaging system while recording respiration were retrospectively analyzed from patients receiving radiotherapy for non-small-cell lung carcinoma. Projection images spanning an approximately 30 degrees gantry arc were sorted into four respiration phase bins prior to DTS reconstruction, which uses a backprojection, followed by a procedure to suppress structures above and below the reconstruction plane of interest. The DTS images were reconstructed in planes at different depths through the patient and normal to a user-selected angle close to the center of the arc. The localization accuracy of RC-DTS was assessed via a comparison with CBCT. Evaluation of RC-DTS in eight tumors shows visible reduction in image blur caused by the respiratory motion. It also allows the visualization of tumor motion extent. The best image quality is achieved at the end-exhalation phase of the respiratory motion. Comparison of RC-DTS with respiration-correlated cone-beam CT in determining tumor position, motion extent and displacement between treatment sessions shows agreement in most cases within 2-3 mm, comparable in magnitude to the intraobserver repeatability of the measurement. These results suggest the method's applicability for soft-tissue image guidance in lung, but must be confirmed with further studies in larger numbers of patients.

Accelerated signal encoding and reconstruction using pixon method

DOEpatents

Puetter, Richard; Yahil, Amos; Pina, Robert

2005-05-17

The method identifies a Pixon element, which is a fundamental and indivisible unit of information, and a Pixon basis, which is the set of possible functions from which the Pixon elements are selected. The actual Pixon elements selected from this basis during the reconstruction process represents the smallest number of such units required to fit the data and representing the minimum number of parameters necessary to specify the image. The Pixon kernels can have arbitrary properties (e.g., shape, size, and/or position) as needed to best fit the data.

Fast l₁-SPIRiT compressed sensing parallel imaging MRI: scalable parallel implementation and clinically feasible runtime.

PubMed

Murphy, Mark; Alley, Marcus; Demmel, James; Keutzer, Kurt; Vasanawala, Shreyas; Lustig, Michael

2012-06-01

We present l₁-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative self-consistent parallel imaging (SPIRiT). Like many iterative magnetic resonance imaging reconstructions, l₁-SPIRiT's image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing l₁-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of l₁-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT spoiled gradient echo (SPGR) sequence with up to 8× acceleration via Poisson-disc undersampling in the two phase-encoded directions.

Carbon contamination analysis and its effect on extreme ultra violet mask imaging performance using coherent scattering microscopy/in-situ accelerated contamination system.

PubMed

Jeong, Chang Young; Lee, Sangsul; Doh, Jong Gul; Lee, Jae Uk; Cha, Han-sun; Nichols, William T; Lee, Dong Gun; Kim, Seong Sue; Cho, Han Ku; Rah, Seung-yu; Ahn, Jinho

2011-07-01

The coherent scattering microscopy/in-situ accelerated contamination system (CSM/ICS) is a developmental metrology tool designed to analyze the impact of carbon contamination on the imaging performance. It was installed at 11B EUVL beam-line of the Pohang Accelerator Laboratory (PAL). Monochromatized 13.5 nm wavelength beam with Mo/Si multilayer mirrors and zirconium filters was used. The CSM/ICS is composed of the CSM for measuring imaging properties and the ICS for implementing acceleration of carbon contamination. The CSM has been proposed as an actinic inspection technique that records the coherent diffraction pattern from the EUV mask and reconstructs its aerial image using a phase retrieval algorithm. To improve the CSM measurement accuracy, optical and electrical noises of main chamber were minimized. The background noise level measured by CCD camera was approximately 8.5 counts (3 sigma) when the EUV beam was off. Actinic CD measurement repeatability was <1 A (3 sigma) at 17.5 nm line and space pattern. The influence of carbon contamination on the imaging properties can be analyzed by transferring EUV mask to CSM imaging center position after executing carbon contamination without a fine alignment system. We also installed photodiode and ellipsometry for in-situ reflectivity and thickness measurement. This paper describes optical design and system performance observed during the first phase of integration, including CSM imaging performance and carbon contamination analysis results.

Accelerated 1 H MRSI using randomly undersampled spiral-based k-space trajectories.

PubMed

Chatnuntawech, Itthi; Gagoski, Borjan; Bilgic, Berkin; Cauley, Stephen F; Setsompop, Kawin; Adalsteinsson, Elfar

2014-07-30

To develop and evaluate the performance of an acquisition and reconstruction method for accelerated MR spectroscopic imaging (MRSI) through undersampling of spiral trajectories. A randomly undersampled spiral acquisition and sensitivity encoding (SENSE) with total variation (TV) regularization, random SENSE+TV, is developed and evaluated on single-slice numerical phantom, in vivo single-slice MRSI, and in vivo three-dimensional (3D)-MRSI at 3 Tesla. Random SENSE+TV was compared with five alternative methods for accelerated MRSI. For the in vivo single-slice MRSI, random SENSE+TV yields up to 2.7 and 2 times reduction in root-mean-square error (RMSE) of reconstructed N-acetyl aspartate (NAA), creatine, and choline maps, compared with the denoised fully sampled and uniformly undersampled SENSE+TV methods with the same acquisition time, respectively. For the in vivo 3D-MRSI, random SENSE+TV yields up to 1.6 times reduction in RMSE, compared with uniform SENSE+TV. Furthermore, by using random SENSE+TV, we have demonstrated on the in vivo single-slice and 3D-MRSI that acceleration factors of 4.5 and 4 are achievable with the same quality as the fully sampled data, as measured by RMSE of reconstructed NAA map, respectively. With the same scan time, random SENSE+TV yields lower RMSEs of metabolite maps than other methods evaluated. Random SENSE+TV achieves up to 4.5-fold acceleration with comparable data quality as the fully sampled acquisition. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model.

PubMed

Ting, Samuel T; Ahmad, Rizwan; Jin, Ning; Craft, Jason; Serafim da Silveira, Juliana; Xue, Hui; Simonetti, Orlando P

2017-04-01

Sparsity-promoting regularizers can enable stable recovery of highly undersampled magnetic resonance imaging (MRI), promising to improve the clinical utility of challenging applications. However, lengthy computation time limits the clinical use of these methods, especially for dynamic MRI with its large corpus of spatiotemporal data. Here, we present a holistic framework that utilizes the balanced sparse model for compressive sensing and parallel computing to reduce the computation time of cardiac MRI recovery methods. We propose a fast, iterative soft-thresholding method to solve the resulting ℓ1-regularized least squares problem. In addition, our approach utilizes a parallel computing environment that is fully integrated with the MRI acquisition software. The methodology is applied to two formulations of the multichannel MRI problem: image-based recovery and k-space-based recovery. Using measured MRI data, we show that, for a 224 × 144 image series with 48 frames, the proposed k-space-based approach achieves a mean reconstruction time of 2.35 min, a 24-fold improvement compared a reconstruction time of 55.5 min for the nonlinear conjugate gradient method, and the proposed image-based approach achieves a mean reconstruction time of 13.8 s. Our approach can be utilized to achieve fast reconstruction of large MRI datasets, thereby increasing the clinical utility of reconstruction techniques based on compressed sensing. Magn Reson Med 77:1505-1515, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Computer generated hologram from point cloud using graphics processor.

PubMed

Chen, Rick H-Y; Wilkinson, Timothy D

2009-12-20

Computer generated holography is an extremely demanding and complex task when it comes to providing realistic reconstructions with full parallax, occlusion, and shadowing. We present an algorithm designed for data-parallel computing on modern graphics processing units to alleviate the computational burden. We apply Gaussian interpolation to create a continuous surface representation from discrete input object points. The algorithm maintains a potential occluder list for each individual hologram plane sample to keep the number of visibility tests to a minimum. We experimented with two approximations that simplify and accelerate occlusion computation. It is observed that letting several neighboring hologram plane samples share visibility information on object points leads to significantly faster computation without causing noticeable artifacts in the reconstructed images. Computing a reduced sample set via nonuniform sampling is also found to be an effective acceleration technique.

Neutron Imaging Camera

NASA Technical Reports Server (NTRS)

Hunter, Stanley; deNolfo, G. A.; Barbier, L. M.; Link, J. T.; Son, S.; Floyd, S. R.; Guardala, N.; Skopec, M.; Stark, B.

2008-01-01

The Neutron Imaging Camera (NIC) is based on the Three-dimensional Track Imager (3DTI) technology developed at GSFC for gamma-ray astrophysics applications. The 3-DTI, a large volume time-projection chamber, provides accurate, approximately 0.4 mm resolution, 3-D tracking of charged particles. The incident direction of fast neutrons, En > 0.5 MeV, are reconstructed from the momenta and energies of the proton and triton fragments resulting from (sup 3)He(n,p) (sup 3)H interactions in the 3-DTI volume. The performance of the NIC from laboratory and accelerator tests is presented.

A Simple Application of Compressed Sensing to Further Accelerate Partially Parallel Imaging

PubMed Central

Miao, Jun; Guo, Weihong; Narayan, Sreenath; Wilson, David L.

2012-01-01

Compressed Sensing (CS) and partially parallel imaging (PPI) enable fast MR imaging by reducing the amount of k-space data required for reconstruction. Past attempts to combine these two have been limited by the incoherent sampling requirement of CS, since PPI routines typically sample on a regular (coherent) grid. Here, we developed a new method, “CS+GRAPPA,” to overcome this limitation. We decomposed sets of equidistant samples into multiple random subsets. Then, we reconstructed each subset using CS, and averaging the results to get a final CS k-space reconstruction. We used both a standard CS, and an edge and joint-sparsity guided CS reconstruction. We tested these intermediate results on both synthetic and real MR phantom data, and performed a human observer experiment to determine the effectiveness of decomposition, and to optimize the number of subsets. We then used these CS reconstructions to calibrate the GRAPPA complex coil weights. In vivo parallel MR brain and heart data sets were used. An objective image quality evaluation metric, Case-PDM, was used to quantify image quality. Coherent aliasing and noise artifacts were significantly reduced using two decompositions. More decompositions further reduced coherent aliasing and noise artifacts but introduced blurring. However, the blurring was effectively minimized using our new edge and joint-sparsity guided CS using two decompositions. Numerical results on parallel data demonstrated that the combined method greatly improved image quality as compared to standard GRAPPA, on average halving Case-PDM scores across a range of sampling rates. The proposed technique allowed the same Case-PDM scores as standard GRAPPA, using about half the number of samples. We conclude that the new method augments GRAPPA by combining it with CS, allowing CS to work even when the k-space sampling pattern is equidistant. PMID:22902065

Coupling reconstruction and motion estimation for dynamic MRI through optical flow constraint

NASA Astrophysics Data System (ADS)

Zhao, Ningning; O'Connor, Daniel; Gu, Wenbo; Ruan, Dan; Basarab, Adrian; Sheng, Ke

2018-03-01

This paper addresses the problem of dynamic magnetic resonance image (DMRI) reconstruction and motion estimation jointly. Because of the inherent anatomical movements in DMRI acquisition, reconstruction of DMRI using motion estimation/compensation (ME/MC) has been explored under the compressed sensing (CS) scheme. In this paper, by embedding the intensity based optical flow (OF) constraint into the traditional CS scheme, we are able to couple the DMRI reconstruction and motion vector estimation. Moreover, the OF constraint is employed in a specific coarse resolution scale in order to reduce the computational complexity. The resulting optimization problem is then solved using a primal-dual algorithm due to its efficiency when dealing with nondifferentiable problems. Experiments on highly accelerated dynamic cardiac MRI with multiple receiver coils validate the performance of the proposed algorithm.

AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting.

PubMed

Cline, Christopher C; Chen, Xiao; Mailhe, Boris; Wang, Qiu; Pfeuffer, Josef; Nittka, Mathias; Griswold, Mark A; Speier, Peter; Nadar, Mariappan S

2017-09-01

Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, additional regularization, and accelerated dictionary search methods. The pipeline described here, accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF), was evaluated with simulations as well as phantom and in vivo scans. We found that the AIR-MRF pipeline provided reduced parameter estimation errors compared to non-iterative and other iterative methods, particularly at shorter sequence lengths. Accelerated dictionary search methods incorporated into the iterative pipeline reduced the reconstruction time at little cost of quality. Copyright © 2017 Elsevier Inc. All rights reserved.

Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging.

PubMed

Holdsworth, Samantha J; Aksoy, Murat; Newbould, Rexford D; Yeom, Kristen; Van, Anh T; Ooi, Melvyn B; Barnes, Patrick D; Bammer, Roland; Skare, Stefan

2012-10-01

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion. The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation. This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data. Copyright © 2012 Wiley Periodicals, Inc.

Accelerated radial Fourier-velocity encoding using compressed sensing.

PubMed

Hilbert, Fabian; Wech, Tobias; Hahn, Dietbert; Köstler, Herbert

2014-09-01

Phase Contrast Magnetic Resonance Imaging (MRI) is a tool for non-invasive determination of flow velocities inside blood vessels. Because Phase Contrast MRI only measures a single mean velocity per voxel, it is only applicable to vessels significantly larger than the voxel size. In contrast, Fourier Velocity Encoding measures the entire velocity distribution inside a voxel, but requires a much longer acquisition time. For accurate diagnosis of stenosis in vessels on the scale of spatial resolution, it is important to know the velocity distribution of a voxel. Our aim was to determine velocity distributions with accelerated Fourier Velocity Encoding in an acquisition time required for a conventional Phase Contrast image. We imaged the femoral artery of healthy volunteers with ECG-triggered, radial CINE acquisition. Data acquisition was accelerated by undersampling, while missing data were reconstructed by Compressed Sensing. Velocity spectra of the vessel were evaluated by high resolution Phase Contrast images and compared to spectra from fully sampled and undersampled Fourier Velocity Encoding. By means of undersampling, it was possible to reduce the scan time for Fourier Velocity Encoding to the duration required for a conventional Phase Contrast image. Acquisition time for a fully sampled data set with 12 different Velocity Encodings was 40 min. By applying a 12.6-fold retrospective undersampling, a data set was generated equal to 3:10 min acquisition time, which is similar to a conventional Phase Contrast measurement. Velocity spectra from fully sampled and undersampled Fourier Velocity Encoded images are in good agreement and show the same maximum velocities as compared to velocity maps from Phase Contrast measurements. Compressed Sensing proved to reliably reconstruct Fourier Velocity Encoded data. Our results indicate that Fourier Velocity Encoding allows an accurate determination of the velocity distribution in vessels in the order of the voxel size. Thus, compared to normal Phase Contrast measurements delivering only mean velocities, no additional scan time is necessary to retrieve meaningful velocity spectra in small vessels. Copyright © 2013. Published by Elsevier GmbH.

Single-shot magnetic resonance spectroscopic imaging with partial parallel imaging.

PubMed

Posse, Stefan; Otazo, Ricardo; Tsai, Shang-Yueh; Yoshimoto, Akio Ernesto; Lin, Fa-Hsuan

2009-03-01

A magnetic resonance spectroscopic imaging (MRSI) pulse sequence based on proton-echo-planar-spectroscopic-imaging (PEPSI) is introduced that measures two-dimensional metabolite maps in a single excitation. Echo-planar spatial-spectral encoding was combined with interleaved phase encoding and parallel imaging using SENSE to reconstruct absorption mode spectra. The symmetrical k-space trajectory compensates phase errors due to convolution of spatial and spectral encoding. Single-shot MRSI at short TE was evaluated in phantoms and in vivo on a 3-T whole-body scanner equipped with a 12-channel array coil. Four-step interleaved phase encoding and fourfold SENSE acceleration were used to encode a 16 x 16 spatial matrix with a 390-Hz spectral width. Comparison with conventional PEPSI and PEPSI with fourfold SENSE acceleration demonstrated comparable sensitivity per unit time when taking into account g-factor-related noise increases and differences in sampling efficiency. LCModel fitting enabled quantification of inositol, choline, creatine, and N-acetyl-aspartate (NAA) in vivo with concentration values in the ranges measured with conventional PEPSI and SENSE-accelerated PEPSI. Cramer-Rao lower bounds were comparable to those obtained with conventional SENSE-accelerated PEPSI at the same voxel size and measurement time. This single-shot MRSI method is therefore suitable for applications that require high temporal resolution to monitor temporal dynamics or to reduce sensitivity to tissue movement.

[The effect of mandibular distraction on the maxilla growth in children with hemifacial microsomia].

PubMed

Yang, Renkai; Tang, Xiaojun; Shi, Lei; Yin, Lin; Yang, Bin; Yin, Hongyu; Liu, Wei; Zhang, Zhiyong

2014-11-01

To analyze the effect of mandibular distraction on the maxilla growth in children with hemifacial microsomia through measurement with the posterior-anterior cephalometric X-ray films and Three-dimensional CT reconstruction images. The deviation angular of maxilla occlusion plane and nasal base plane from the infra-orbital plane were measured on the posterior-anterior cephalometric X-ray films in 22 patients before and half a year after operation. The vertical distance from the midpoint of 5th teeth alveolar and the lowest point of maxillary sinus to reference plane were measured on 3D reconstruction images in 15 patients. The data were statistically analyzed. On posterior-anterior cephalometric X-ray films, the cant of occlusion plane were significantly reduced (P < 0.05), While the angular of nasal base plane and the infra-orbital plane had no significant change. On 3D reconstruction images, all the detection points had significantly declined except the lowest point of maxillary sinus on normal side. Distraction osteogenesis of mandible can promote the growth of the maxilla in children with HFM, the accelerated growth parts include alveolar bone and maxillary sinus.

Accelerating free breathing myocardial perfusion MRI using multi coil radial k - t SLR

NASA Astrophysics Data System (ADS)

Goud Lingala, Sajan; DiBella, Edward; Adluru, Ganesh; McGann, Christopher; Jacob, Mathews

2013-10-01

The clinical utility of myocardial perfusion MR imaging (MPI) is often restricted by the inability of current acquisition schemes to simultaneously achieve high spatio-temporal resolution, good volume coverage, and high signal to noise ratio. Moreover, many subjects often find it difficult to hold their breath for sufficiently long durations making it difficult to obtain reliable MPI data. Accelerated acquisition of free breathing MPI data can overcome some of these challenges. Recently, an algorithm termed as k - t SLR has been proposed to accelerate dynamic MRI by exploiting sparsity and low rank properties of dynamic MRI data. The main focus of this paper is to further improve k - t SLR and demonstrate its utility in considerably accelerating free breathing MPI. We extend its previous implementation to account for multi-coil radial MPI acquisitions. We perform k - t sampling experiments to compare different radial trajectories and determine the best sampling pattern. We also introduce a novel augmented Lagrangian framework to considerably improve the algorithm’s convergence rate. The proposed algorithm is validated using free breathing rest and stress radial perfusion data sets from two normal subjects and one patient with ischemia. k - t SLR was observed to provide faithful reconstructions at high acceleration levels with minimal artifacts compared to existing MPI acceleration schemes such as spatio-temporal constrained reconstruction and k - t SPARSE/SENSE.

Accelerating free breathing myocardial perfusion MRI using multi coil radial k-t SLR

PubMed Central

Lingala, Sajan Goud; DiBella, Edward; Adluru, Ganesh; McGann, Christopher; Jacob, Mathews

2013-01-01

The clinical utility of myocardial perfusion MR imaging (MPI) is often restricted by the inability of current acquisition schemes to simultaneously achieve high spatio-temporal resolution, good volume coverage, and high signal to noise ratio. Moreover, many subjects often find it difficult to hold their breath for sufficiently long durations making it difficult to obtain reliable MPI data. Accelerated acquisition of free breathing MPI data can overcome some of these challenges. Recently, an algorithm termed as k − t SLR has been proposed to accelerate dynamic MRI by exploiting sparsity and low rank properties of dynamic MRI data. The main focus of this paper is to further improve k − t SLR and demonstrate its utility in considerably accelerating free breathing MPI. We extend its previous implementation to account for multi-coil radial MPI acquisitions. We perform k − t sampling experiments to compare different radial trajectories and determine the best sampling pattern. We also introduce a novel augmented Lagrangian framework to considerably improve the algorithm's convergence rate. The proposed algorithm is validated using free breathing rest and stress radial perfusion data sets from two normal subjects and one patient with ischemia. k − t SLR was observed to provide faithful reconstructions at high acceleration levels with minimal artifacts compared to existing MPI acceleration schemes such as spatio-temporal constrained reconstruction (STCR) and k − t SPARSE/SENSE. PMID:24077063

Fast ℓ1-SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime

PubMed Central

Murphy, Mark; Alley, Marcus; Demmel, James; Keutzer, Kurt; Vasanawala, Shreyas; Lustig, Michael

2012-01-01

We present ℓ1-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the Wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative Self-Consistent Parallel Imaging (SPIRiT). Like many iterative MRI reconstructions, ℓ1-SPIRiT’s image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing ℓ1-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of ℓ1-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT Spoiled Gradient Echo (SPGR) sequence with up to 8× acceleration via poisson-disc undersampling in the two phase-encoded directions. PMID:22345529

Compressed sensing reconstruction of cardiac cine MRI using golden angle spiral trajectories

NASA Astrophysics Data System (ADS)

Tolouee, Azar; Alirezaie, Javad; Babyn, Paul

2015-11-01

In dynamic cardiac cine Magnetic Resonance Imaging (MRI), the spatiotemporal resolution is limited by the low imaging speed. Compressed sensing (CS) theory has been applied to improve the imaging speed and thus the spatiotemporal resolution. The purpose of this paper is to improve CS reconstruction of under sampled data by exploiting spatiotemporal sparsity and efficient spiral trajectories. We extend k-t sparse algorithm to spiral trajectories to achieve high spatio temporal resolutions in cardiac cine imaging. We have exploited spatiotemporal sparsity of cardiac cine MRI by applying a 2D + time wavelet-Fourier transform. For efficient coverage of k-space, we have used a modified version of multi shot (interleaved) spirals trajectories. In order to reduce incoherent aliasing artifact, we use different random undersampling pattern for each temporal frame. Finally, we have used nonuniform fast Fourier transform (NUFFT) algorithm to reconstruct the image from the non-uniformly acquired samples. The proposed approach was tested in simulated and cardiac cine MRI data. Results show that higher acceleration factors with improved image quality can be obtained with the proposed approach in comparison to the existing state-of-the-art method. The flexibility of the introduced method should allow it to be used not only for the challenging case of cardiac imaging, but also for other patient motion where the patient moves or breathes during acquisition.

3D ultrasound computer tomography: update from a clinical study

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Kretzek, E.; Henrich, J.; Tukalo, A.; Gemmeke, H.; Kaiser, C.; Knaudt, J.; Ruiter, N. V.

2016-04-01

Ultrasound Computer Tomography (USCT) is a promising new imaging method for breast cancer diagnosis. We developed a 3D USCT system and tested it in a pilot study with encouraging results: 3D USCT was able to depict two carcinomas, which were present in contrast enhanced MRI volumes serving as ground truth. To overcome severe differences in the breast shape, an image registration was applied. We analyzed the correlation between average sound speed in the breast and the breast density estimated from segmented MRIs and found a positive correlation with R=0.70. Based on the results of the pilot study we now carry out a successive clinical study with 200 patients. For this we integrated our reconstruction methods and image post-processing into a comprehensive workflow. It includes a dedicated DICOM viewer for interactive assessment of fused USCT images. A new preview mode now allows intuitive and faster patient positioning. We updated the USCT system to decrease the data acquisition time by approximately factor two and to increase the penetration depth of the breast into the USCT aperture by 1 cm. Furthermore the compute-intensive reflectivity reconstruction was considerably accelerated, now allowing a sub-millimeter volume reconstruction in approximately 16 minutes. The updates made it possible to successfully image first patients in our ongoing clinical study.

Electron tomography of HEK293T cells using scanning electron microscope-based scanning transmission electron microscopy.

PubMed

You, Yun-Wen; Chang, Hsun-Yun; Liao, Hua-Yang; Kao, Wei-Lun; Yen, Guo-Ji; Chang, Chi-Jen; Tsai, Meng-Hung; Shyue, Jing-Jong

2012-10-01

Based on a scanning electron microscope operated at 30 kV with a homemade specimen holder and a multiangle solid-state detector behind the sample, low-kV scanning transmission electron microscopy (STEM) is presented with subsequent electron tomography for three-dimensional (3D) volume structure. Because of the low acceleration voltage, the stronger electron-atom scattering leads to a stronger contrast in the resulting image than standard TEM, especially for light elements. Furthermore, the low-kV STEM yields less radiation damage to the specimen, hence the structure can be preserved. In this work, two-dimensional STEM images of a 1-μm-thick cell section with projection angles between ±50° were collected, and the 3D volume structure was reconstructed using the simultaneous iterative reconstructive technique algorithm with the TomoJ plugin for ImageJ, which are both public domain software. Furthermore, the cross-sectional structure was obtained with the Volume Viewer plugin in ImageJ. Although the tilting angle is constrained and limits the resulting structural resolution, slicing the reconstructed volume generated the depth profile of the thick specimen with sufficient resolution to examine cellular uptake of Au nanoparticles, and the final position of these nanoparticles inside the cell was imaged.

A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

PubMed

Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

2014-06-21

As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

A model-based reconstruction for undersampled radial spin echo DTI with variational penalties on the diffusion tensor

PubMed Central

Knoll, Florian; Raya, José G; Halloran, Rafael O; Baete, Steven; Sigmund, Eric; Bammer, Roland; Block, Tobias; Otazo, Ricardo; Sodickson, Daniel K

2015-01-01

Radial spin echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled DTI. A model-based reconstruction implicitly exploits redundancies in the diffusion weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a Total Variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (3 and 2 volunteers, respectively). Evaluation of the new approach was conducted by comparing the results to reconstructions performed with gridding, combined parallel imaging and compressed sensing, and a recently proposed model-based approach. The experiments demonstrated improvement in terms of reduction of noise and streaking artifacts in the quantitative parameter maps as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin echo diffusion tensor imaging without degrading parameter quantification and/or SNR. PMID:25594167

Imaging industry expectations for compressed sensing in MRI

NASA Astrophysics Data System (ADS)

King, Kevin F.; Kanwischer, Adriana; Peters, Rob

2015-09-01

Compressed sensing requires compressible data, incoherent acquisition and a nonlinear reconstruction algorithm to force creation of a compressible image consistent with the acquired data. MRI images are compressible using various transforms (commonly total variation or wavelets). Incoherent acquisition of MRI data by appropriate selection of pseudo-random or non-Cartesian locations in k-space is straightforward. Increasingly, commercial scanners are sold with enough computing power to enable iterative reconstruction in reasonable times. Therefore integration of compressed sensing into commercial MRI products and clinical practice is beginning. MRI frequently requires the tradeoff of spatial resolution, temporal resolution and volume of spatial coverage to obtain reasonable scan times. Compressed sensing improves scan efficiency and reduces the need for this tradeoff. Benefits to the user will include shorter scans, greater patient comfort, better image quality, more contrast types per patient slot, the enabling of previously impractical applications, and higher throughput. Challenges to vendors include deciding which applications to prioritize, guaranteeing diagnostic image quality, maintaining acceptable usability and workflow, and acquisition and reconstruction algorithm details. Application choice depends on which customer needs the vendor wants to address. The changing healthcare environment is putting cost and productivity pressure on healthcare providers. The improved scan efficiency of compressed sensing can help alleviate some of this pressure. Image quality is strongly influenced by image compressibility and acceleration factor, which must be appropriately limited. Usability and workflow concerns include reconstruction time and user interface friendliness and response. Reconstruction times are limited to about one minute for acceptable workflow. The user interface should be designed to optimize workflow and minimize additional customer training. Algorithm concerns include the decision of which algorithms to implement as well as the problem of optimal setting of adjustable parameters. It will take imaging vendors several years to work through these challenges and provide solutions for a wide range of applications.

Clinical application of Half Fourier Acquisition Single Shot Turbo Spin Echo (HASTE) imaging accelerated by simultaneous multi-slice acquisition.

PubMed

Schulz, Jenni; P Marques, José; Ter Telgte, Annemieke; van Dorst, Anouk; de Leeuw, Frank-Erik; Meijer, Frederick J A; Norris, David G

2018-01-01

As a single-shot sequence with a long train of refocusing pulses, Half-Fourier Acquisition Single-Shot Turbo-Spin-Echo (HASTE) suffers from high power deposition limiting use at high resolutions and high field strengths, particularly if combined with acceleration techniques such as simultaneous multi-slice (SMS) imaging. Using a combination of multiband (MB)-excitation and PINS-refocusing pulses will effectively accelerate the acquisition time while staying within the SAR limitations. In particular, uncooperative and young patients will profit from the speed of the MB-PINS HASTE sequence, as clinical diagnosis can be possible without sedation. Materials and MethodsMB-excitation and PINS-refocusing pulses were incorporated into a HASTE-sequence with blipped CAIPIRINHA and TRAPS including an internal FLASH reference scan for online reconstruction. Whole brain MB-PINS HASTE data were acquired on a Siemens 3T-Prisma system from 10 individuals and compared to a clinical HASTE protocol. ResultsThe proposed MB-PINS HASTE protocol accelerates the acquisition by about a factor 2 compared to the clinical HASTE. The diagnostic image quality proved to be comparable for both sequences for the evaluation of the overall aspect of the brain, the detection of white matter changes and areas of tissue loss, and for the evaluation of the CSF spaces although artifacts were more frequently encountered with MB-PINS HASTE. ConclusionsMB-PINS HASTE enables acquisition of slice accelerated highly T2-weighted images and provides good diagnostic image quality while reducing acquisition time. Copyright © 2017 Elsevier B.V. All rights reserved.

Max CAPR: high-resolution 3D contrast-enhanced MR angiography with acquisition times under 5 seconds.

PubMed

Haider, Clifton R; Borisch, Eric A; Glockner, James F; Mostardi, Petrice M; Rossman, Phillip J; Young, Phillip M; Riederer, Stephen J

2010-10-01

High temporal and spatial resolution is desired in imaging of vascular abnormalities having short arterial-to-venous transit times. Methods that exploit temporal correlation to reduce the observed frame time demonstrate temporal blurring, obfuscating bolus dynamics. Previously, a Cartesian acquisition with projection reconstruction-like (CAPR) sampling method has been demonstrated for three-dimensional contrast-enhanced angiographic imaging of the lower legs using two-dimensional sensitivity-encoding acceleration and partial Fourier acceleration, providing 1mm isotropic resolution of the calves, with 4.9-sec frame time and 17.6-sec temporal footprint. In this work, the CAPR acquisition is further undersampled to provide a net acceleration approaching 40 by eliminating all view sharing. The tradeoff of frame time and temporal footprint in view sharing is presented and characterized in phantom experiments. It is shown that the resultant 4.9-sec acquisition time, three-dimensional images sets have sufficient spatial and temporal resolution to clearly portray arterial and venous phases of contrast passage. It is further hypothesized that these short temporal footprint sequences provide diagnostic quality images. This is tested and shown in a series of nine contrast-enhanced MR angiography patient studies performed with the new method.

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick, John C.; Imaging, Lawson Health Research Institute, Knoxville, TN; London Regional Cancer Program, Knoxville, TN

2014-08-15

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process.more » Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions.« less

Three-dimensional self-gated cardiac MR imaging for the evaluation of myocardial infarction in mouse model on a 3T clinical MR system.

PubMed

Zhang, Xiaoyong; Qiu, Bensheng; Wei, Zijun; Yan, Fei; Shi, Caiyun; Su, Shi; Liu, Xin; Ji, Jim X; Xie, Guoxi

2017-01-01

To develop and assess a three-dimensional (3D) self-gated technique for the evaluation of myocardial infarction (MI) in mouse model without the use of external electrocardiogram (ECG) trigger and respiratory motion sensor on a 3T clinical MR system. A 3D T1-weighted GRE sequence with stack-of-stars sampling trajectories was developed and performed on six mice with MIs that were injected with a gadolinium-based contrast agent at a 3T clinical MR system. Respiratory and cardiac self-gating signals were derived from the Cartesian mapping of the k-space center along the partition encoding direction by bandpass filtering in image domain. The data were then realigned according to the predetermined self-gating signals for the following image reconstruction. In order to accelerate the data acquisition, image reconstruction was based on compressed sensing (CS) theory by exploiting temporal sparsity of the reconstructed images. In addition, images were also reconstructed from the same realigned data by conventional regridding method for demonstrating the advantageous of the proposed reconstruction method. Furthermore, the accuracy of detecting MI by the proposed method was assessed using histological analysis as the standard reference. Linear regression and Bland-Altman analysis were used to assess the agreement between the proposed method and the histological analysis. Compared to the conventional regridding method, the proposed CS method reconstructed images with much less streaking artifact, as well as a better contrast-to-noise ratio (CNR) between the blood and myocardium (4.1 ± 2.1 vs. 2.9 ± 1.1, p = 0.031). Linear regression and Bland-Altman analysis demonstrated that excellent correlation was obtained between infarct sizes derived from the proposed method and histology analysis. A 3D T1-weighted self-gating technique for mouse cardiac imaging was developed, which has potential for accurately evaluating MIs in mice at 3T clinical MR system without the use of external ECG trigger and respiratory motion sensor.

Low-dose megavoltage cone-beam computed tomography for lung tumors using a high-efficiency image receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sillanpaa, Jussi; Chang Jenghwa; Mageras, Gikas

2006-09-15

We report on the capabilities of a low-dose megavoltage cone-beam computed tomography (MV CBCT) system. The high-efficiency image receptor consists of a photodiode array coupled to a scintillator composed of individual CsI crystals. The CBCT system uses the 6 MV beam from a linear accelerator. A synchronization circuit allows us to limit the exposure to one beam pulse [0.028 monitor units (MU)] per projection image. 150-500 images (4.2-13.9 MU total) are collected during a one-minute scan and reconstructed using a filtered backprojection algorithm. Anthropomorphic and contrast phantoms are imaged and the contrast-to-noise ratio of the reconstruction is studied as amore » function of the number of projections and the error in the projection angles. The detector dose response is linear (R{sup 2} value 0.9989). A 2% electron density difference is discernible using 460 projection images and a total exposure of 13 MU (corresponding to a maximum absorbed dose of about 12 cGy in a patient). We present first patient images acquired with this system. Tumors in lung are clearly visible and skeletal anatomy is observed in sufficient detail to allow reproducible registration with the planning kV CT images. The MV CBCT system is shown to be capable of obtaining good quality three-dimensional reconstructions at relatively low dose and to be clinically usable for improving the accuracy of radiotherapy patient positioning.« less

Image reconstruction algorithms for electrical capacitance tomography based on ROF model using new numerical techniques

NASA Astrophysics Data System (ADS)

Chen, Jiaoxuan; Zhang, Maomao; Liu, Yinyan; Chen, Jiaoliao; Li, Yi

2017-03-01

Electrical capacitance tomography (ECT) is a promising technique applied in many fields. However, the solutions for ECT are not unique and highly sensitive to the measurement noise. To remain a good shape of reconstructed object and endure a noisy data, a Rudin-Osher-Fatemi (ROF) model with total variation regularization is applied to image reconstruction in ECT. Two numerical methods, which are simplified augmented Lagrangian (SAL) and accelerated alternating direction method of multipliers (AADMM), are innovatively introduced to try to solve the above mentioned problems in ECT. The effect of the parameters and the number of iterations for different algorithms, and the noise level in capacitance data are discussed. Both simulation and experimental tests were carried out to validate the feasibility of the proposed algorithms, compared to the Landweber iteration (LI) algorithm. The results show that the SAL and AADMM algorithms can handle a high level of noise and the AADMM algorithm outperforms other algorithms in identifying the object from its background.

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

DOE PAGES

Pryor, Alan; Ophus, Colin; Miao, Jianwei

2017-10-25

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. In this paper, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditionalmore » multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.« less

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy.

PubMed

Pryor, Alan; Ophus, Colin; Miao, Jianwei

2017-01-01

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditional multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic , using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic .

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pryor, Alan; Ophus, Colin; Miao, Jianwei

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. In this paper, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditionalmore » multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.« less

A novel algorithm for the reconstruction of an entrance beam fluence from treatment exit patient portal dosimetry images

NASA Astrophysics Data System (ADS)

Sperling, Nicholas Niven

The problem of determining the in vivo dosimetry for patients undergoing radiation treatment has been an area of interest since the development of the field. Most methods which have found clinical acceptance work by use of a proxy dosimeter, e.g.: glass rods, using radiophotoluminescence; thermoluminescent dosimeters (TLD), typically CaF or LiF; Metal Oxide Silicon Field Effect Transistor (MOSFET) dosimeters, using threshold voltage shift; Optically Stimulated Luminescent Dosimeters (OSLD), composed of Carbon doped Aluminum Dioxide crystals; RadioChromic film, using leuko-dye polymers; Silicon Diode dosimeters, typically p-type; and ion chambers. More recent methods employ Electronic Portal Image Devices (EPID), or dosimeter arrays, for entrance or exit beam fluence determination. The difficulty with the proxy in vivo dosimetery methods is the requirement that they be placed at the particular location where the dose is to be determined. This precludes measurements across the entire patient volume. These methods are best suited where the dose at a particular location is required. The more recent methods of in vivo dosimetry make use of detector arrays and reconstruction techniques to determine dose throughout the patient volume. One method uses an array of ion chambers located upstream of the patient. This requires a special hardware device and places an additional attenuator in the beam path, which may not be desirable. A final approach is to use the existing EPID, which is part of most modern linear accelerators, to image the patient using the treatment beam. Methods exist to deconvolve the detector function of the EPID using a series of weighted exponentials. Additionally, this method has been extended to determine in vivo dosimetry. The method developed here employs the use of EPID images and an iterative deconvolution algorithm to reconstruct the impinging primary beam fluence on the patient. This primary fluence may then be employed to determine dose through the entire patient volume. The method requires patient specific information, including a CT for deconvolution/dose reconstruction. With the large-scale adoption of Cone Beam CT (CBCT) systems on modern linear accelerators, a treatment time CT is readily available for use in this deconvolution and in dose representation.

Exploiting sparsity and low-rank structure for the recovery of multi-slice breast MRIs with reduced sampling error.

PubMed

Yin, X X; Ng, B W-H; Ramamohanarao, K; Baghai-Wadji, A; Abbott, D

2012-09-01

It has been shown that, magnetic resonance images (MRIs) with sparsity representation in a transformed domain, e.g. spatial finite-differences (FD), or discrete cosine transform (DCT), can be restored from undersampled k-space via applying current compressive sampling theory. The paper presents a model-based method for the restoration of MRIs. The reduced-order model, in which a full-system-response is projected onto a subspace of lower dimensionality, has been used to accelerate image reconstruction by reducing the size of the involved linear system. In this paper, the singular value threshold (SVT) technique is applied as a denoising scheme to reduce and select the model order of the inverse Fourier transform image, and to restore multi-slice breast MRIs that have been compressively sampled in k-space. The restored MRIs with SVT for denoising show reduced sampling errors compared to the direct MRI restoration methods via spatial FD, or DCT. Compressive sampling is a technique for finding sparse solutions to underdetermined linear systems. The sparsity that is implicit in MRIs is to explore the solution to MRI reconstruction after transformation from significantly undersampled k-space. The challenge, however, is that, since some incoherent artifacts result from the random undersampling, noise-like interference is added to the image with sparse representation. These recovery algorithms in the literature are not capable of fully removing the artifacts. It is necessary to introduce a denoising procedure to improve the quality of image recovery. This paper applies a singular value threshold algorithm to reduce the model order of image basis functions, which allows further improvement of the quality of image reconstruction with removal of noise artifacts. The principle of the denoising scheme is to reconstruct the sparse MRI matrices optimally with a lower rank via selecting smaller number of dominant singular values. The singular value threshold algorithm is performed by minimizing the nuclear norm of difference between the sampled image and the recovered image. It has been illustrated that this algorithm improves the ability of previous image reconstruction algorithms to remove noise artifacts while significantly improving the quality of MRI recovery.

Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment.

PubMed

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-12-01

Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT∕CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT∕CT reconstruction algorithm. Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process. An ultrafast, reliable and scalable 4D CBCT∕CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment.

Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment

PubMed Central

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-01-01

Purpose: Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT/CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. Methods: In this work, we accelerated the Feldcamp–Davis–Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT/CT reconstruction algorithm. Results: Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10−7. Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process. Conclusions: An ultrafast, reliable and scalable 4D CBCT/CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment. PMID:22149842

A fast multi-resolution approach to tomographic PIV

NASA Astrophysics Data System (ADS)

Discetti, Stefano; Astarita, Tommaso

2012-03-01

Tomographic particle image velocimetry (Tomo-PIV) is a recently developed three-component, three-dimensional anemometric non-intrusive measurement technique, based on an optical tomographic reconstruction applied to simultaneously recorded images of the distribution of light intensity scattered by seeding particles immersed into the flow. Nowadays, the reconstruction process is carried out mainly by iterative algebraic reconstruction techniques, well suited to handle the problem of limited number of views, but computationally intensive and memory demanding. The adoption of the multiplicative algebraic reconstruction technique (MART) has become more and more accepted. In the present work, a novel multi-resolution approach is proposed, relying on the adoption of a coarser grid in the first step of the reconstruction to obtain a fast estimation of a reliable and accurate first guess. A performance assessment, carried out on three-dimensional computer-generated distributions of particles, shows a substantial acceleration of the reconstruction process for all the tested seeding densities with respect to the standard method based on 5 MART iterations; a relevant reduction in the memory storage is also achieved. Furthermore, a slight accuracy improvement is noticed. A modified version, improved by a multiplicative line of sight estimation of the first guess on the compressed configuration, is also tested, exhibiting a further remarkable decrease in both memory storage and computational effort, mostly at the lowest tested seeding densities, while retaining the same performances in terms of accuracy.

GPU-Accelerated Hybrid Algorithm for 3D Localization of Fluorescent Emitters in Dense Clusters

NASA Astrophysics Data System (ADS)

Jung, Yoon; Barsic, Anthony; Piestun, Rafael; Fakhri, Nikta

In stochastic switching-based super-resolution imaging, a random subset of fluorescent emitters are imaged and localized for each frame to construct a single high resolution image. However, the condition of non-overlapping point spread functions (PSFs) imposes constraints on experimental parameters. Recent development in post processing methods such as dictionary-based sparse support recovery using compressive sensing has shown up to an order of magnitude higher recall rate than single emitter fitting methods. However, the computational complexity of this approach scales poorly with the grid size and requires long runtime. Here, we introduce a fast and accurate compressive sensing algorithm for localizing fluorescent emitters in high density in 3D, namely sparse support recovery using Orthogonal Matching Pursuit (OMP) and L1-Homotopy algorithm for reconstructing STORM images (SOLAR STORM). SOLAR STORM combines OMP with L1-Homotopy to reduce computational complexity, which is further accelerated by parallel implementation using GPUs. This method can be used in a variety of experimental conditions for both in vitro and live cell fluorescence imaging.

MO-DE-210-06: Development of a Supercompounded 3D Volumetric Ultrasound Image Guidance System for Prone Accelerated Partial Breast Irradiation (APBI)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, T; Hrycushko, B; Zhao, B

2015-06-15

Purpose: For early-stage breast cancer, accelerated partial breast irradiation (APBI) is a cost-effective breast-conserving treatment. Irradiation in a prone position can mitigate respiratory induced breast movement and achieve maximal sparing of heart and lung tissues. However, accurate dose delivery is challenging due to breast deformation and lumpectomy cavity shrinkage. We propose a 3D volumetric ultrasound (US) image guidance system for accurate prone APBI Methods: The designed system, set beneath the prone breast board, consists of a water container, an US scanner, and a two-layer breast immobilization cup. The outer layer of the breast cup forms the inner wall of watermore » container while the inner layer is attached to patient breast directly to immobilization. The US transducer scans is attached to the outer-layer of breast cup at the dent of water container. Rotational US scans in a transverse plane are achieved by simultaneously rotating water container and transducer, and multiple transverse scanning forms a 3D scan. A supercompounding-technique-based volumetric US reconstruction algorithm is developed for 3D image reconstruction. The performance of the designed system is evaluated with two custom-made gelatin phantoms containing several cylindrical inserts filled in with water (11% reflection coefficient between materials). One phantom is designed for positioning evaluation while the other is for scaling assessment. Results: In the positioning evaluation phantom, the central distances between the inserts are 15, 20, 30 and 40 mm. The distances on reconstructed images differ by −0.19, −0.65, −0.11 and −1.67 mm, respectively. In the scaling evaluation phantom, inserts are 12.7, 19.05, 25.40 and 31.75 mm in diameter. Measured inserts’ sizes on images differed by 0.23, 0.19, −0.1 and 0.22 mm, respectively. Conclusion: The phantom evaluation results show that the developed 3D volumetric US system can accurately localize target position and determine target volume, and is a promising image-guidance tool for prone APBI.« less

Compressed sensing with gradient total variation for low-dose CBCT reconstruction

NASA Astrophysics Data System (ADS)

Seo, Chang-Woo; Cha, Bo Kyung; Jeon, Seongchae; Huh, Young; Park, Justin C.; Lee, Byeonghun; Baek, Junghee; Kim, Eunyoung

2015-06-01

This paper describes the improvement of convergence speed with gradient total variation (GTV) in compressed sensing (CS) for low-dose cone-beam computed tomography (CBCT) reconstruction. We derive a fast algorithm for the constrained total variation (TV)-based a minimum number of noisy projections. To achieve this task we combine the GTV with a TV-norm regularization term to promote an accelerated sparsity in the X-ray attenuation characteristics of the human body. The GTV is derived from a TV and enforces more efficient computationally and faster in convergence until a desired solution is achieved. The numerical algorithm is simple and derives relatively fast convergence. We apply a gradient projection algorithm that seeks a solution iteratively in the direction of the projected gradient while enforcing a non-negatively of the found solution. In comparison with the Feldkamp, Davis, and Kress (FDK) and conventional TV algorithms, the proposed GTV algorithm showed convergence in ≤18 iterations, whereas the original TV algorithm needs at least 34 iterations in reducing 50% of the projections compared with the FDK algorithm in order to reconstruct the chest phantom images. Future investigation includes improving imaging quality, particularly regarding X-ray cone-beam scatter, and motion artifacts of CBCT reconstruction.

Convex Accelerated Maximum Entropy Reconstruction

PubMed Central

Worley, Bradley

2016-01-01

Maximum entropy (MaxEnt) spectral reconstruction methods provide a powerful framework for spectral estimation of nonuniformly sampled datasets. Many methods exist within this framework, usually defined based on the magnitude of a Lagrange multiplier in the MaxEnt objective function. An algorithm is presented here that utilizes accelerated first-order convex optimization techniques to rapidly and reliably reconstruct nonuniformly sampled NMR datasets using the principle of maximum entropy. This algorithm – called CAMERA for Convex Accelerated Maximum Entropy Reconstruction Algorithm – is a new approach to spectral reconstruction that exhibits fast, tunable convergence in both constant-aim and constant-lambda modes. A high-performance, open source NMR data processing tool is described that implements CAMERA, and brief comparisons to existing reconstruction methods are made on several example spectra. PMID:26894476

Three Element Phased Array Coil for Imaging of Rat Spinal Cord at 7T

PubMed Central

Mogatadakala, Kishore V.; Bankson, James A.; Narayana, Ponnada A.

2008-01-01

In order to overcome some of the limitations of an implantable coil, including its invasive nature and limited spatial coverage, a three element phased array coil is described for high resolution magnetic resonance imaging (MRI) of rat spinal cord. This coil allows imaging both thoracic and cervical segments of rat spinal cord. In the current design, coupling between the nearest neighbors was minimized by overlapping the coil elements. A simple capacitive network was used for decoupling the next neighbor elements. The dimensions of individual coils in the array were determined based on the signal-to-noise ratio (SNR) measurements performed on a phantom with three different surface coils. SNR measurements on a phantom demonstrated higher SNR of the phased array coil relative to two different volume coils. In-vivo images acquired on rat spinal cord with our coil demonstrated excellent gray and white matter contrast. To evaluate the performance of the phased array coil under parallel imaging, g-factor maps were obtained for two different acceleration factors of 2 and 3. These simulations indicate that parallel imaging with acceleration factor of 2 would be possible without significant image reconstruction related noise amplifications. PMID:19025892

SU-E-J-36: Comparison of CBCT Image Quality for Manufacturer Default Imaging Modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, G

Purpose CBCT is being increasingly used in patient setup for radiotherapy. Often the manufacturer default scan modes are used for performing these CBCT scans with the assumption that they are the best options. To quantitatively assess the image quality of these scan modes, all of the scan modes were tested as well as options with the reconstruction algorithm. Methods A CatPhan 504 phantom was scanned on a TrueBeam Linear Accelerator using the manufacturer scan modes (FSRT Head, Head, Image Gently, Pelvis, Pelvis Obese, Spotlight, & Thorax). The Head mode scan was then reconstructed multiple times with all filter options (Smooth,more » Standard, Sharp, & Ultra Sharp) and all Ring Suppression options (Disabled, Weak, Medium, & Strong). An open source ImageJ tool was created for analyzing the CatPhan 504 images. Results The MTF curve was primarily dictated by the voxel size and the filter used in the reconstruction algorithm. The filters also impact the image noise. The CNR was worst for the Image Gently mode, followed by FSRT Head and Head. The sharper the filter, the worse the CNR. HU varied significantly between scan modes. Pelvis Obese had lower than expected HU values than most while the Image Gently mode had higher than expected HU values. If a therapist tried to use preset window and level settings, they would not show the desired tissue for some scan modes. Conclusion Knowing the image quality of the set scan modes, will enable users to better optimize their setup CBCT. Evaluation of the scan mode image quality could improve setup efficiency and lead to better treatment outcomes.« less

Automated ultrafast kilovoltage-megavoltage cone-beam CT for image guided radiotherapy of lung cancer: System description and real-time results.

PubMed

Blessing, Manuel; Arns, Anna; Wertz, Hansjoerg; Stsepankou, Dzmitry; Boda-Heggemann, Judit; Hesser, Juergen; Wenz, Frederik; Lohr, Frank

2018-04-01

To establish a fully automated kV-MV CBCT imaging method on a clinical linear accelerator that allows image acquisition of thoracic targets for patient positioning within one breath-hold (∼15s) under realistic clinical conditions. Our previously developed FPGA-based hardware unit which allows synchronized kV-MV CBCT projection acquisition is connected to a clinical linear accelerator system via a multi-pin switch; i.e. either kV-MV imaging or conventional clinical mode can be selected. An application program was developed to control the relevant linac parameters automatically and to manage the MV detector readout as well as the gantry angle capture for each MV projection. The kV projections are acquired with the conventional CBCT system. GPU-accelerated filtered backprojection is performed separately for both data sets. After appropriate grayscale normalization both modalities are combined and the final kV-MV volume is re-imported in the CBCT system to enable image matching. To demonstrate adequate geometrical accuracy of the novel imaging system the Penta-Guide phantom QA procedure is performed. Furthermore, a human plastinate and different tumor shapes in a thorax phantom are scanned. Diameters of the known tumor shapes are measured in the kV-MV reconstruction. An automated kV-MV CBCT workflow was successfully established in a clinical environment. The overall procedure, from starting the data acquisition until the reconstructed volume is available for registration, requires ∼90s including 17s acquisition time for 100° rotation. It is very simple and allows target positioning in the same way as for conventional CBCT. Registration accuracy of the QA phantom is within ±1mm. The average deviation from the known tumor dimensions measured in the thorax phantom was 0.7mm which corresponds to an improvement of 36% compared to our previous kV-MV imaging system. Due to automation the kV-MV CBCT workflow is speeded up by a factor of >10 compared to the manual approach. Thus, the system allows a simple, fast and reliable imaging procedure and fulfills all requirements to be successfully introduced into the clinical workflow now, enabling single-breath-hold volume imaging. Copyright © 2018. Published by Elsevier GmbH.

Compressed sensing for high-resolution nonlipid suppressed 1 H FID MRSI of the human brain at 9.4T.

PubMed

Nassirpour, Sahar; Chang, Paul; Avdievitch, Nikolai; Henning, Anke

2018-04-29

The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra-short TR and TE 1 H FID MRSI sequence at 9.4T. X-t sparse compressed sensing reconstruction was optimized for nonlipid suppressed 1 H FID MRSI data. Coil-by-coil x-t sparse reconstruction was compared with SENSE x-t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared. Coil-by-coil x-t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x-t sparse). For acceleration factors of up to 5, both the low-rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved. By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min. © 2018 International Society for Magnetic Resonance in Medicine.

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

NASA Technical Reports Server (NTRS)

Xu, Feng; Deshpande, Manohar

2012-01-01

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: Cone/ring artifact correction and multiple GPU implementation

PubMed Central

Yan, Hao; Wang, Xiaoyu; Shi, Feng; Bai, Ti; Folkerts, Michael; Cervino, Laura; Jiang, Steve B.; Jia, Xun

2014-01-01

Purpose: Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior–inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT). Methods: Image quality improvement methods are proposed to mitigate the cone and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases. Results: Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior–inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases. Conclusions: The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation. PMID:25370645

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: Cone/ring artifact correction and multiple GPU implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Hao, E-mail: steve.jiang@utsouthwestern.edu, E-mail: xun.jia@utsouthwestern.edu; Shi, Feng; Jiang, Steve B.

Purpose: Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior–inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT). Methods: Image quality improvement methods are proposed to mitigate the conemore » and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases. Results: Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior–inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases. Conclusions: The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation.« less

Extra projection data identification method for fast-continuous-rotation industrial cone-beam CT.

PubMed

Yang, Min; Duan, Shengling; Duan, Jinghui; Wang, Xiaolong; Li, Xingdong; Meng, Fanyong; Zhang, Jianhai

2013-01-01

Fast-continuous-rotation is an effective measure to improve the scanning speed and decrease the radiation dose for cone-beam CT. However, because of acceleration and deceleration of the motor, as well as the response lag of the scanning control terminals to the host PC, uneven-distributed and redundant projections are inevitably created, which seriously decrease the quality of the reconstruction images. In this paper, we first analyzed the aspects of the theoretical sequence chart of the fast-continuous-rotation mode. Then, an optimized sequence chart was proposed by extending the rotation angle span to ensure the effective 2π-span projections were situated in the stable rotation stage. In order to match the rotation angle with the projection image accurately, structure similarity (SSIM) index was used as a control parameter for extraction of the effective projection sequence which was exactly the complete projection data for image reconstruction. The experimental results showed that SSIM based method had a high accuracy of projection view locating and was easy to realize.

Extended hybrid-space SENSE for EPI: Off-resonance and eddy current corrected joint interleaved blip-up/down reconstruction.

PubMed

Zahneisen, Benjamin; Aksoy, Murat; Maclaren, Julian; Wuerslin, Christian; Bammer, Roland

2017-06-01

Geometric distortions along the phase encode direction caused by off-resonant spins are still a major issue in EPI based functional and diffusion imaging. If the off-resonance map is known it is possible to correct for distortions. Most correction methods operate as a post-processing step on the reconstructed magnitude images. Here, we present an algebraic reconstruction method (hybrid-space SENSE) that incorporates a physics based model of off-resonances, phase inconsistencies between k-space segments, and T2*-decay during the acquisition. The method can be used to perform a joint reconstruction of interleaved acquisitions with normal (blip-up) and inverted (blip-down) phase encode direction which results in reduced g-factor penalty. A joint blip-up/down simultaneous multi slice (SMS) reconstruction for SMS-factor 4 in combination with twofold in-plane acceleration leads to a factor of two decrease in maximum g-factor penalty while providing off-resonance and eddy-current corrected images. We provide an algebraic framework for reconstructing diffusion weighted EPI data that in addition to the general applicability of hybrid-space SENSE to 2D-EPI, SMS-EPI and 3D-EPI with arbitrary k-space coverage along z, allows for a modeling of arbitrary spatio-temporal effects during the acquisition period like off-resonances, phase inconsistencies and T2*-decay. The most immediate benefit is a reduction in g-factor penalty if an interleaved blip-up/down acquisition strategy is chosen which facilitates eddy current estimation and ensures no loss in k-space encoding in regions with strong off-resonance gradients. Copyright © 2017 Elsevier Inc. All rights reserved.

Accelerated short-TE 3D proton echo-planar spectroscopic imaging using 2D-SENSE with a 32-channel array coil.

PubMed

Otazo, Ricardo; Tsai, Shang-Yueh; Lin, Fa-Hsuan; Posse, Stefan

2007-12-01

MR spectroscopic imaging (MRSI) with whole brain coverage in clinically feasible acquisition times still remains a major challenge. A combination of MRSI with parallel imaging has shown promise to reduce the long encoding times and 2D acceleration with a large array coil is expected to provide high acceleration capability. In this work a very high-speed method for 3D-MRSI based on the combination of proton echo planar spectroscopic imaging (PEPSI) with regularized 2D-SENSE reconstruction is developed. Regularization was performed by constraining the singular value decomposition of the encoding matrix to reduce the effect of low-value and overlapped coil sensitivities. The effects of spectral heterogeneity and discontinuities in coil sensitivity across the spectroscopic voxels were minimized by unaliasing the point spread function. As a result the contamination from extracranial lipids was reduced 1.6-fold on average compared to standard SENSE. We show that the acquisition of short-TE (15 ms) 3D-PEPSI at 3 T with a 32 x 32 x 8 spatial matrix using a 32-channel array coil can be accelerated 8-fold (R = 4 x 2) along y-z to achieve a minimum acquisition time of 1 min. Maps of the concentrations of N-acetyl-aspartate, creatine, choline, and glutamate were obtained with moderate reduction in spatial-spectral quality. The short acquisition time makes the method suitable for volumetric metabolite mapping in clinical studies. (c) 2007 Wiley-Liss, Inc.

Evaluation of image compression for computer-aided diagnosis of breast tumors in 3D sonography

NASA Astrophysics Data System (ADS)

Chen, We-Min; Huang, Yu-Len; Tao, Chi-Chuan; Chen, Dar-Ren; Moon, Woo-Kyung

2006-03-01

Medical imaging examinations form the basis for physicians diagnosing diseases, as evidenced by the increasing use of digital medical images for picture archiving and communications systems (PACS). However, with enlarged medical image databases and rapid growth of patients' case reports, PACS requires image compression to accelerate the image transmission rate and conserve disk space for diminishing implementation costs. For this purpose, JPEG and JPEG2000 have been accepted as legal formats for the digital imaging and communications in medicine (DICOM). The high compression ratio is felt to be useful for medical imagery. Therefore, this study evaluates the compression ratios of JPEG and JPEG2000 standards for computer-aided diagnosis (CAD) of breast tumors in 3-D medical ultrasound (US) images. The 3-D US data sets with various compression ratios are compressed using the two efficacious image compression standards. The reconstructed data sets are then diagnosed by a previous proposed CAD system. The diagnostic accuracy is measured based on receiver operating characteristic (ROC) analysis. Namely, the ROC curves are used to compare the diagnostic performance of two or more reconstructed images. Analysis results ensure a comparison of the compression ratios by using JPEG and JPEG2000 for 3-D US images. Results of this study provide the possible bit rates using JPEG and JPEG2000 for 3-D breast US images.

Quantitative comparison of the pivot shift test results before and after anterior cruciate ligament reconstruction by using the three-dimensional electromagnetic measurement system.

PubMed

Nagai, Kanto; Hoshino, Yuichi; Nishizawa, Yuichiro; Araki, Daisuke; Matsushita, Takehiko; Matsumoto, Tomoyuki; Takayama, Koji; Nagamune, Kouki; Kurosaka, Masahiro; Kuroda, Ryosuke

2015-10-01

Tibial acceleration during the pivot shift test is a potential quantitative parameter to evaluate rotational laxity of anterior cruciate ligament (ACL) insufficiency. However, clinical application of this measurement has not been fully examined. This study aimed to measure and compare tibial acceleration before and after ACL reconstruction (ACLR) in ACL-injured patients. We hypothesized tibial acceleration would be reduced by ACLR and tibial acceleration would be consistent in the same knee at different time points. Seventy ACL-injured patients who underwent ACLR were enrolled. Tibial acceleration during the pivot shift test was measured using an electromagnetic measurement system before ALCR and at the second-look arthroscopy 1 year post-operatively. Tibial acceleration was compared to clinical grading and between ACL-injured/ACL-reconstructed and contralateral knees. Pre-operative tibial acceleration was increased stepwise with the increase in clinical grading (P < 0.01). Tibial acceleration in ACL-injured knee (1.9 ± 1.2 m/s(2)) was larger than that in the contralateral knee (0.8 ± 0.3 m/s(2), P < 0.01), and reduced to 0.9 ± 0.3 m/s(2) post-operatively (P < 0.01). There was no difference between ACL-reconstructed and contralateral knee (n.s.). Tibial acceleration in contralateral knees was consistent pre- and post-operatively (n.s.). Tibial acceleration measurement demonstrated increased rotational laxity in ACL-injured knees and its reduction by ALCR. Additionally, consistent measurements were obtained in ACL-intact knees at different time points. Therefore, tibial acceleration during the pivot shift test could provide quantitative evaluation of rotational stability before and after ACL reconstruction. III.

Multiplexed phase-space imaging for 3D fluorescence microscopy.

PubMed

Liu, Hsiou-Yuan; Zhong, Jingshan; Waller, Laura

2017-06-26

Optical phase-space functions describe spatial and angular information simultaneously; examples of optical phase-space functions include light fields in ray optics and Wigner functions in wave optics. Measurement of phase-space enables digital refocusing, aberration removal and 3D reconstruction. High-resolution capture of 4D phase-space datasets is, however, challenging. Previous scanning approaches are slow, light inefficient and do not achieve diffraction-limited resolution. Here, we propose a multiplexed method that solves these problems. We use a spatial light modulator (SLM) in the pupil plane of a microscope in order to sequentially pattern multiplexed coded apertures while capturing images in real space. Then, we reconstruct the 3D fluorescence distribution of our sample by solving an inverse problem via regularized least squares with a proximal accelerated gradient descent solver. We experimentally reconstruct a 101 Megavoxel 3D volume (1010×510×500µm with NA 0.4), demonstrating improved acquisition time, light throughput and resolution compared to scanning aperture methods. Our flexible patterning scheme further allows sparsity in the sample to be exploited for reduced data capture.

Waveform inversion with source encoding for breast sound speed reconstruction in ultrasound computed tomography.

PubMed

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the sound speed distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Both computer simulation and experimental phantom studies are conducted to demonstrate the use of the WISE method. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Analysis of Cultural Heritage by Accelerator Techniques and Analytical Imaging

NASA Astrophysics Data System (ADS)

Ide-Ektessabi, Ari; Toque, Jay Arre; Murayama, Yusuke

2011-12-01

In this paper we present the result of experimental investigation using two very important accelerator techniques: (1) synchrotron radiation XRF and XAFS; and (2) accelerator mass spectrometry and multispectral analytical imaging for the investigation of cultural heritage. We also want to introduce a complementary approach to the investigation of artworks which is noninvasive and nondestructive that can be applied in situ. Four major projects will be discussed to illustrate the potential applications of these accelerator and analytical imaging techniques: (1) investigation of Mongolian Textile (Genghis Khan and Kublai Khan Period) using XRF, AMS and electron microscopy; (2) XRF studies of pigments collected from Korean Buddhist paintings; (3) creating a database of elemental composition and spectral reflectance of more than 1000 Japanese pigments which have been used for traditional Japanese paintings; and (4) visible light-near infrared spectroscopy and multispectral imaging of degraded malachite and azurite. The XRF measurements of the Japanese and Korean pigments could be used to complement the results of pigment identification by analytical imaging through spectral reflectance reconstruction. On the other hand, analysis of the Mongolian textiles revealed that they were produced between 12th and 13th century. Elemental analysis of the samples showed that they contained traces of gold, copper, iron and titanium. Based on the age and trace elements in the samples, it was concluded that the textiles were produced during the height of power of the Mongol empire, which makes them a valuable cultural heritage. Finally, the analysis of the degraded and discolored malachite and azurite demonstrates how multispectral analytical imaging could be used to complement the results of high energy-based techniques.

SU-D-17A-02: Four-Dimensional CBCT Using Conventional CBCT Dataset and Iterative Subtraction Algorithm of a Lung Patient

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, E; Lasio, G; Yi, B

2014-06-01

Purpose: The Iterative Subtraction Algorithm (ISA) method generates retrospectively a pre-selected motion phase cone-beam CT image from the full motion cone-beam CT acquired at standard rotation speed. This work evaluates ISA method with real lung patient data. Methods: The goal of the ISA algorithm is to extract motion and no- motion components form the full reconstruction CBCT. The workflow consists of subtracting from the full CBCT all of the undesired motion phases and obtain a motion de-blurred single-phase CBCT image, followed by iteration of this subtraction process. ISA is realized as follows: 1) The projections are sorted to various phases,more » and from all phases, a full reconstruction is performed to generate an image CTM. 2) Generate forward projections of CTM at the desired phase projection angles, the subtraction of projection and the forward projection will reconstruct a CTSub1, which diminishes the desired phase component. 3) By adding back the CTSub1 to CTm, no motion CBCT, CTS1, can be computed. 4) CTS1 still contains residual motion component. 5) This residual motion component can be further reduced by iteration.The ISA 4DCBCT technique was implemented using Varian Trilogy accelerator OBI system. To evaluate the method, a lung patient CBCT dataset was used. The reconstruction algorithm is FDK. Results: The single phase CBCT reconstruction generated via ISA successfully isolates the desired motion phase from the full motion CBCT, effectively reducing motion blur. It also shows improved image quality, with reduced streak artifacts with respect to the reconstructions from unprocessed phase-sorted projections only. Conclusion: A CBCT motion de-blurring algorithm, ISA, has been developed and evaluated with lung patient data. The algorithm allows improved visualization of a single phase motion extracted from a standard CBCT dataset. This study has been supported by National Institute of Health through R01CA133539.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Ying D.; Yang, Zhongwei; Wang, Rui

On 2012 September 30-October 1 the Earth underwent a two-step geomagnetic storm. We examine the Sun-to-Earth characteristics of the coronal mass ejections (CMEs) responsible for the geomagnetic storm with combined heliospheric imaging and in situ observations. The first CME, which occurred on 2012 September 25, is a slow event and shows an acceleration followed by a nearly invariant speed in the whole Sun-Earth space. The second event, launched from the Sun on 2012 September 27, exhibits a quick acceleration, then a rapid deceleration, and finally a nearly constant speed, a typical Sun-to-Earth propagation profile for fast CMEs. These two CMEsmore » interacted near 1 AU as predicted by the heliospheric imaging observations and formed a complex ejecta observed at Wind, with a shock inside that enhanced the pre-existing southward magnetic field. Reconstruction of the complex ejecta with the in situ data indicates an overall left-handed flux-rope-like configuration with an embedded concave-outward shock front, a maximum magnetic field strength deviating from the flux rope axis, and convex-outward field lines ahead of the shock. While the reconstruction results are consistent with the picture of CME-CME interactions, a magnetic cloud-like structure without clear signs of CME interactions is anticipated when the merging process is finished.« less

Recent Developments and Applications of Radiation/Detection Technology in Tsinghua University

NASA Astrophysics Data System (ADS)

Kang, Ke-Jun

2010-03-01

Nuclear technology applications have been very important research fields in Tsinghua University (THU) for more than 50 years. This paper describes two major directions and related projects running in THU concerning nuclear technology applications for radiation imaging and nuclear technology applications for astrophysics. Radiation imaging is a significant application of nuclear technology for all kinds of real world needs including security inspections, anti-smuggling operations, and medicine. The current improved imaging systems give much higher quality radiation images. THU has produced accelerating tubes for both industrial and medical accelerators with energy levels ranging from 2.5˜20Mev. Detectors have been produced for medical and industrial imaging as well as for high energy physics experiments such as the MRPC with fast time and position resolutions. DR and CT systems for radiation imaging systems have been continuously improved with new system designs and improved algorithms for image reconstruction and processing. Two important new key initiatives are the dual-energy radiography and dual-energy CT systems. Dual-energy CT imaging improves material discrimination by providing both the electron density and the atomic number distribution of scanned objects. Finally, this paper also introduces recent developments related to the hard X-ray modulation telescope (HXMT) provided by THU.

Vibration measurement by temporal Fourier analyses of a digital hologram sequence.

PubMed

Fu, Yu; Pedrini, Giancarlo; Osten, Wolfgang

2007-08-10

A method for whole-field noncontact measurement of displacement, velocity, and acceleration of a vibrating object based on image-plane digital holography is presented. A series of digital holograms of a vibrating object are captured by use of a high-speed CCD camera. The result of the reconstruction is a three-dimensional complex-valued matrix with noise. We apply Fourier analysis and windowed Fourier analysis in both the spatial and the temporal domains to extract the displacement, the velocity, and the acceleration. The instantaneous displacement is obtained by temporal unwrapping of the filtered phase map, whereas the velocity and acceleration are evaluated by Fourier analysis and by windowed Fourier analysis along the time axis. The combination of digital holography and temporal Fourier analyses allows for evaluation of the vibration, without a phase ambiguity problem, and smooth spatial distribution of instantaneous displacement, velocity, and acceleration of each instant are obtained. The comparison of Fourier analysis and windowed Fourier analysis in velocity and acceleration measurements is also presented.

Using learned under-sampling pattern for increasing speed of cardiac cine MRI based on compressive sensing principles

NASA Astrophysics Data System (ADS)

Zamani, Pooria; Kayvanrad, Mohammad; Soltanian-Zadeh, Hamid

2012-12-01

This article presents a compressive sensing approach for reducing data acquisition time in cardiac cine magnetic resonance imaging (MRI). In cardiac cine MRI, several images are acquired throughout the cardiac cycle, each of which is reconstructed from the raw data acquired in the Fourier transform domain, traditionally called k-space. In the proposed approach, a majority, e.g., 62.5%, of the k-space lines (trajectories) are acquired at the odd time points and a minority, e.g., 37.5%, of the k-space lines are acquired at the even time points of the cardiac cycle. Optimal data acquisition at the even time points is learned from the data acquired at the odd time points. To this end, statistical features of the k-space data at the odd time points are clustered by fuzzy c-means and the results are considered as the states of Markov chains. The resulting data is used to train hidden Markov models and find their transition matrices. Then, the trajectories corresponding to transition matrices far from an identity matrix are selected for data acquisition. At the end, an iterative thresholding algorithm is used to reconstruct the images from the under-sampled k-space datasets. The proposed approaches for selecting the k-space trajectories and reconstructing the images generate more accurate images compared to alternative methods. The proposed under-sampling approach achieves an acceleration factor of 2 for cardiac cine MRI.

Leveraging EAP-Sparsity for Compressed Sensing of MS-HARDI in (k, q)-Space.

PubMed

Sun, Jiaqi; Sakhaee, Elham; Entezari, Alireza; Vemuri, Baba C

2015-01-01

Compressed Sensing (CS) for the acceleration of MR scans has been widely investigated in the past decade. Lately, considerable progress has been made in achieving similar speed ups in acquiring multi-shell high angular resolution diffusion imaging (MS-HARDI) scans. Existing approaches in this context were primarily concerned with sparse reconstruction of the diffusion MR signal S(q) in the q-space. More recently, methods have been developed to apply the compressed sensing framework to the 6-dimensional joint (k, q)-space, thereby exploiting the redundancy in this 6D space. To guarantee accurate reconstruction from partial MS-HARDI data, the key ingredients of compressed sensing that need to be brought together are: (1) the function to be reconstructed needs to have a sparse representation, and (2) the data for reconstruction ought to be acquired in the dual domain (i.e., incoherent sensing) and (3) the reconstruction process involves a (convex) optimization. In this paper, we present a novel approach that uses partial Fourier sensing in the 6D space of (k, q) for the reconstruction of P(x, r). The distinct feature of our approach is a sparsity model that leverages surfacelets in conjunction with total variation for the joint sparse representation of P(x, r). Thus, our method stands to benefit from the practical guarantees for accurate reconstruction from partial (k, q)-space data. Further, we demonstrate significant savings in acquisition time over diffusion spectral imaging (DSI) which is commonly used as the benchmark for comparisons in reported literature. To demonstrate the benefits of this approach,.we present several synthetic and real data examples.

Rapid anatomical brain imaging using spiral acquisition and an expanded signal model.

PubMed

Kasper, Lars; Engel, Maria; Barmet, Christoph; Haeberlin, Maximilian; Wilm, Bertram J; Dietrich, Benjamin E; Schmid, Thomas; Gross, Simon; Brunner, David O; Stephan, Klaas E; Pruessmann, Klaas P

2018-03-01

We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B 0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T 2 * contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency. Copyright © 2017 Elsevier Inc. All rights reserved.

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

NASA Astrophysics Data System (ADS)

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

Technical note: RabbitCT--an open platform for benchmarking 3D cone-beam reconstruction algorithms.

PubMed

Rohkohl, C; Keck, B; Hofmann, H G; Hornegger, J

2009-09-01

Fast 3D cone beam reconstruction is mandatory for many clinical workflows. For that reason, researchers and industry work hard on hardware-optimized 3D reconstruction. Backprojection is a major component of many reconstruction algorithms that require a projection of each voxel onto the projection data, including data interpolation, before updating the voxel value. This step is the bottleneck of most reconstruction algorithms and the focus of optimization in recent publications. A crucial limitation, however, of these publications is that the presented results are not comparable to each other. This is mainly due to variations in data acquisitions, preprocessing, and chosen geometries and the lack of a common publicly available test dataset. The authors provide such a standardized dataset that allows for substantial comparison of hardware accelerated backprojection methods. They developed an open platform RabbitCT (www.rabbitCT.com) for worldwide comparison in backprojection performance and ranking on different architectures using a specific high resolution C-arm CT dataset of a rabbit. This includes a sophisticated benchmark interface, a prototype implementation in C++, and image quality measures. At the time of writing, six backprojection implementations are already listed on the website. Optimizations include multithreading using Intel threading building blocks and OpenMP, vectorization using SSE, and computation on the GPU using CUDA 2.0. There is a need for objectively comparing backprojection implementations for reconstruction algorithms. RabbitCT aims to provide a solution to this problem by offering an open platform with fair chances for all participants. The authors are looking forward to a growing community and await feedback regarding future evaluations of novel software- and hardware-based acceleration schemes.

GPU-accelerated iterative reconstruction from Compton scattered data using a matched pair of conic projector and backprojector.

PubMed

Nguyen, Van-Giang; Lee, Soo-Jin

2016-07-01

Iterative reconstruction from Compton scattered data is known to be computationally more challenging than that from conventional line-projection based emission data in that the gamma rays that undergo Compton scattering are modeled as conic projections rather than line projections. In conventional tomographic reconstruction, to parallelize the projection and backprojection operations using the graphics processing unit (GPU), approximated methods that use an unmatched pair of ray-tracing forward projector and voxel-driven backprojector have been widely used. In this work, we propose a new GPU-accelerated method for Compton camera reconstruction which is more accurate by using exactly matched pair of projector and backprojector. To calculate conic forward projection, we first sample the cone surface into conic rays and accumulate the intersecting chord lengths of the conic rays passing through voxels using a fast ray-tracing method (RTM). For conic backprojection, to obtain the true adjoint of the conic forward projection, while retaining the computational efficiency of the GPU, we use a voxel-driven RTM which is essentially the same as the standard RTM used for the conic forward projector. Our simulation results show that, while the new method is about 3 times slower than the approximated method, it is still about 16 times faster than the CPU-based method without any loss of accuracy. The net conclusion is that our proposed method is guaranteed to retain the reconstruction accuracy regardless of the number of iterations by providing a perfectly matched projector-backprojector pair, which makes iterative reconstruction methods for Compton imaging faster and more accurate. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A comprehensive study on decreasing the kilovoltage cone-beam CT dose by reducing the projection number.

PubMed

Lu, Bo; Lu, Haibin; Palta, Jatinder

2010-05-12

The objective of this study was to evaluate the effect of kilovoltage cone-beam computed tomography (CBCT) on registration accuracy and image qualities with a reduced number of planar projections used in volumetric imaging reconstruction. The ultimate goal is to evaluate the possibility of reducing the patient dose while maintaining registration accuracy under different projection-number schemes for various clinical sites. An Elekta Synergy Linear accelerator with an onboard CBCT system was used in this study. The quality of the Elekta XVI cone-beam three-dimensional volumetric images reconstructed with a decreasing number of projections was quantitatively evaluated by a Catphan phantom. Subsequently, we tested the registration accuracy of imaging data sets on three rigid anthropomorphic phantoms and three real patient sites under the reduced projection-number (as low as 1/6th) reconstruction of CBCT data with different rectilinear shifts and rota-tions. CBCT scan results of the Catphan phantom indicated the CBCT images got noisier when the number of projections was reduced, but their spatial resolution and uniformity were hardly affected. The maximum registration errors under the small amount transformation of the reference CT images were found to be within 0.7 mm translation and 0.3 masculine rotation. However, when the projection number was lower than one-fourth of the full set with a large amount of transformation of reference CT images, the registration could easily be trapped into local minima solutions for a nonrigid anatomy. We concluded, by using projection-number reduction strategy under conscientious care, imaging-guided localization procedure could achieve a lower patient dose without losing the registration accuracy for various clinical sites and situations. A faster scanning time is the main advantage compared to the mA decrease-based, dose-reduction method.

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Toward atomic-scale bright-field electron tomography for the study of fullerene-like nanostructures.

PubMed

Bar Sadan, Maya; Houben, Lothar; Wolf, Sharon G; Enyashin, Andrey; Seifert, Gotthard; Tenne, Reshef; Urban, Knut

2008-03-01

We present the advancement of electron tomography for three-dimensional structure reconstruction of fullerene-like particles toward atomic-scale resolution. The three-dimensional reconstruction of nested molybdenum disulfide nanooctahedra is achieved by the combination of low voltage operation of the electron microscope with aberration-corrected phase contrast imaging. The method enables the study of defects and irregularities in the three-dimensional structure of individual fullerene-like particles on the scale of 2-3 A. Control over shape, size, and atomic architecture is a key issue in synthesis and design of functional nanoparticles. Transmission electron microscopy (TEM) is the primary technique to characterize materials down to the atomic level, albeit the images are two-dimensional projections of the studied objects. Recent advancements in aberration-corrected TEM have demonstrated single atom sensitivity for light elements at subångström resolution. Yet, the resolution of tomographic schemes for three-dimensional structure reconstruction has not surpassed 1 nm3, preventing it from becoming a powerful tool for characterization in the physical sciences on the atomic scale. Here we demonstrate that negative spherical aberration imaging at low acceleration voltage enables tomography down to the atomic scale at reduced radiation damage. First experimental data on the three-dimensional reconstruction of nested molybdenum disulfide nanooctahedra is presented. The method is applicable to the analysis of the atomic architecture of a wide range of nanostructures where strong electron channeling is absent, in particular to carbon fullerenes and inorganic fullerenes.

Accelerating cine-MR Imaging in Mouse Hearts Using Compressed Sensing

PubMed Central

Wech, Tobias; Lemke, Angela; Medway, Debra; Stork, Lee-Anne; Lygate, Craig A; Neubauer, Stefan; Köstler, Herbert; Schneider, Jürgen E

2011-01-01

Purpose To combine global cardiac function imaging with compressed sensing (CS) in order to reduce scan time and to validate this technique in normal mouse hearts and in a murine model of chronic myocardial infarction. Materials and Methods To determine the maximally achievable acceleration factor, fully acquired cine data, obtained in sham and chronically infarcted (MI) mouse hearts were 2–4-fold undersampled retrospectively, followed by CS reconstruction and blinded image segmentation. Subsequently, dedicated CS sampling schemes were implemented at a preclinical 9.4 T magnetic resonance imaging (MRI) system, and 2- and 3-fold undersampled cine data were acquired in normal mouse hearts with high temporal and spatial resolution. Results The retrospective analysis demonstrated that an undersampling factor of three is feasible without impairing accuracy of cardiac functional parameters. Dedicated CS sampling schemes applied prospectively to normal mouse hearts yielded comparable left-ventricular functional parameters, and intra- and interobserver variability between fully and 3-fold undersampled data. Conclusion This study introduces and validates an alternative means to speed up experimental cine-MRI without the need for expensive hardware. J. Magn. Reson. Imaging 2011. © 2011 Wiley Periodicals, Inc. PMID:21932360

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method.

PubMed

Lee, Danny; Greer, Peter B; Pollock, Sean; Kim, Taeho; Keall, Paul

2016-05-01

The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

Anterior Cruciate Ligament-Derived Stem Cells Transduced With BMP2 Accelerate Graft-Bone Integration After ACL Reconstruction.

PubMed

Kawakami, Yohei; Takayama, Koji; Matsumoto, Tomoyuki; Tang, Ying; Wang, Bing; Mifune, Yutaka; Cummins, James H; Warth, Ryan J; Kuroda, Ryosuke; Kurosaka, Masahiro; Fu, Freddie H; Huard, Johnny

2017-03-01

Strong graft-bone integration is a prerequisite for successful graft remodeling after reconstruction of the anterior cruciate ligament (ACL) using soft tissue grafts. Novel strategies to accelerate soft tissue graft-bone integration are needed to reduce the need for bone-tendon-bone graft harvest, reduce patient convalescence, facilitate rehabilitation, and reduce total recovery time after ACL reconstruction. The application of ACL-derived stem cells with enhanced expression of bone morphogenetic protein 2 (BMP2) onto soft tissue grafts in the form of cell sheets will both accelerate and improve the quality of graft-bone integration after ACL reconstruction in a rat model. Controlled laboratory study. ACL-derived CD34+ cells were isolated from remnant human ACL tissues, virally transduced to express BMP2, and embedded within cell sheets. In a rat model of ACL injury, bilateral single-bundle ACL reconstructions were performed, in which cell sheets were wrapped around tendon autografts before reconstruction. Four groups containing a total of 48 rats (96 knees) were established (n = 12 rats; 24 knees per group): CD34+BMP2 (100%), CD34+BMP2 (25%), CD34+ (untransduced), and a control group containing no cells. Six rats from each group were euthanized 2 and 4 weeks after surgery, and each graft was harvested for immunohistochemical and histological analyses. The remaining 6 rats in each group were euthanized at 4 and 8 weeks to evaluate in situ tensile load to failure in each femur-graft-tibia complex. In vitro, BMP2 transduction promoted the osteogenic differentiation of ACL-derived CD34+ cells while retaining their intrinsic multipotent capabilities. Osteoblast densities were greatest in the BMP2 (100%) and BMP2 (25%) groups. Bone tunnels in the CD34+BMP2 (100%) and CD34+BMP2 (25%) groups had the smallest cross-sectional areas according to micro-computed tomography analyses. Graft-bone integration occurred most rapidly in the CD34+BMP2 (25%) group. Tensile load to failure was significantly greater in the groups containing stem cells at 4 and 8 weeks after surgery. Tensile strength was greatest in the CD34+BMP2 (100%) group at 4 weeks, and in the CD34+BMP2 (25%) group at 8 weeks. ACL-derived CD34+ cells transduced with BMP2 accelerated graft-bone integration after ACL reconstruction using soft tissue autografts in a rat model, as evidenced by improved histological appearance and graft-bone interface biology along with tensile load to failure at each time point up to 8 weeks after surgery. A primary disadvantage of using soft tissue grafts for ACL reconstruction is the prolonged time required for bony ingrowth, which delays the initiation of midsubstance graft remodeling. The lack of consistent correlation between the appearance of a "healed" ACL on postoperative magnetic resonance imaging and readiness to return to sport results in athletes being released to sport before the graft is ready to handle high-intensity loading. Therefore, it is desirable to identify strategies that accelerate graft-bone integration, which would reduce the time to biologic fixation, improve the reliability of biologic fixation, allow for accelerated rehabilitation, and potentially reduce the incidence of early graft pullout and late midsubstance failure.

JDiffraction: A GPGPU-accelerated JAVA library for numerical propagation of scalar wave fields

NASA Astrophysics Data System (ADS)

Piedrahita-Quintero, Pablo; Trujillo, Carlos; Garcia-Sucerquia, Jorge

2017-05-01

JDiffraction, a GPGPU-accelerated JAVA library for numerical propagation of scalar wave fields, is presented. Angular spectrum, Fresnel transform, and Fresnel-Bluestein transform are the numerical algorithms implemented in the methods and functions of the library to compute the scalar propagation of the complex wavefield. The functionality of the library is tested with the modeling of easy to forecast numerical experiments and also with the numerical reconstruction of a digitally recorded hologram. The performance of JDiffraction is contrasted with a library written for C++, showing great competitiveness in the apparently less complex environment of JAVA language. JDiffraction also includes JAVA easy-to-use methods and functions that take advantage of the computation power of the graphic processing units to accelerate the processing times of 2048×2048 pixel images up to 74 frames per second.

Single-shot imaging with higher-dimensional encoding using magnetic field monitoring and concomitant field correction.

PubMed

Testud, Frederik; Gallichan, Daniel; Layton, Kelvin J; Barmet, Christoph; Welz, Anna M; Dewdney, Andrew; Cocosco, Chris A; Pruessmann, Klaas P; Hennig, Jürgen; Zaitsev, Maxim

2015-03-01

PatLoc (Parallel Imaging Technique using Localized Gradients) accelerates imaging and introduces a resolution variation across the field-of-view. Higher-dimensional encoding employs more spatial encoding magnetic fields (SEMs) than the corresponding image dimensionality requires, e.g. by applying two quadratic and two linear spatial encoding magnetic fields to reconstruct a 2D image. Images acquired with higher-dimensional single-shot trajectories can exhibit strong artifacts and geometric distortions. In this work, the source of these artifacts is analyzed and a reliable correction strategy is derived. A dynamic field camera was built for encoding field calibration. Concomitant fields of linear and nonlinear spatial encoding magnetic fields were analyzed. A combined basis consisting of spherical harmonics and concomitant terms was proposed and used for encoding field calibration and image reconstruction. A good agreement between the analytical solution for the concomitant fields and the magnetic field simulations of the custom-built PatLoc SEM coil was observed. Substantial image quality improvements were obtained using a dynamic field camera for encoding field calibration combined with the proposed combined basis. The importance of trajectory calibration for single-shot higher-dimensional encoding is demonstrated using the combined basis including spherical harmonics and concomitant terms, which treats the concomitant fields as an integral part of the encoding. © 2014 Wiley Periodicals, Inc.

Assessment of the impact of modeling axial compression on PET image reconstruction.

PubMed

Belzunce, Martin A; Reader, Andrew J

2017-10-01

To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher frequencies. Modeling the axial compression also achieved a lower coefficient of variation but with an increase of intervoxel correlations. The unmatched projector/backprojector achieved similar contrast values to the matched version at considerably lower reconstruction times, but at the cost of noisier images. For a line source scan, the reconstructions with modeling of the axial compression achieved similar resolution to the span 1 reconstructions. Axial compression applied to PET sinograms was found to have a negligible impact for span values lower than 7. For span values up to 21, the spatial resolution degradation due to the axial compression can be almost completely compensated for by modeling this effect in the system matrix at the expense of considerably larger processing times and higher intervoxel correlations, while retaining the storage benefit of compressed data. For even higher span values, the resolution loss cannot be completely compensated possibly due to an effective null space in the system. The use of an unmatched projector/backprojector proved to be a practical solution to compensate for the spatial resolution degradation at a reasonable computational cost but can lead to noisier images. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Three-dimensional sinus imaging as an adjunct to two-dimensional imaging to accelerate education and improve spatial orientation.

PubMed

Yao, William C; Regone, Rachel M; Huyhn, Nancy; Butler, E Brian; Takashima, Masayoshi

2014-03-01

Develop a novel three-dimensional (3-D) anatomical model to assist in improving spatial knowledge of the skull base, paranasal sinuses, and adjacent structures, and validate the utilization of 3-D reconstruction to augment two-dimensional (2-D) computed tomography (CT) for the training of medical students and otolaryngology-head and neck surgery residents. Prospective study. A study of 18 subjects studying sinus anatomy was conducted at a tertiary academic center during the 2011 to 2012 academic year. An image processing and 3-D modeling program was used to create a color coded 3-D scalable/layerable/rotatable model of key paranasal and skull base structures from a 2-D high-resolution sinus CT scan. Subjects received instruction of the sinus anatomy in two sessions, first through review of a 2-D CT sinus scan, followed by an educational module of the 3-D reconstruction. After each session, subjects rated their knowledge of the sinus and adjacent structures on a self-assessment questionnaire. Significant improvement in the perceived understanding of the anatomy was noted after the 3-D educational module session when compared to the 2-D CT session alone (P < .01). Every subject believed the addition of 3-D imaging accelerated their education of sinus anatomy and recommended its use to others. The impression of the learners was that a 3-D educational module, highlighting key structures, is a highly effective tool to enhance the education of medical students and otolaryngology residents in sinus and skull base anatomy and its adjacent structures, specifically in conceptualizing the spatial orientation of these structures. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Fast 3D magnetic resonance fingerprinting for a whole-brain coverage.

PubMed

Ma, Dan; Jiang, Yun; Chen, Yong; McGivney, Debra; Mehta, Bhairav; Gulani, Vikas; Griswold, Mark

2018-04-01

The purpose of this study was to accelerate the acquisition and reconstruction time of 3D magnetic resonance fingerprinting scans. A 3D magnetic resonance fingerprinting scan was accelerated by using a single-shot spiral trajectory with an undersampling factor of 48 in the x-y plane, and an interleaved sampling pattern with an undersampling factor of 3 through plane. Further acceleration came from reducing the waiting time between neighboring partitions. The reconstruction time was accelerated by applying singular value decomposition compression in k-space. Finally, a 3D premeasured B 1 map was used to correct for the B 1 inhomogeneity. The T 1 and T 2 values of the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI phantom showed a good agreement with the standard values, with an average concordance correlation coefficient of 0.99, and coefficient of variation of 7% in the repeatability scans. The results from in vivo scans also showed high image quality in both transverse and coronal views. This study applied a fast acquisition scheme for a fully quantitative 3D magnetic resonance fingerprinting scan with a total acceleration factor of 144 as compared with the Nyquist rate, such that 3D T 1 , T 2 , and proton density maps can be acquired with whole-brain coverage at clinical resolution in less than 5 min. Magn Reson Med 79:2190-2197, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Magnetic resonance spectroscopic imaging at superresolution: Overview and perspectives

NASA Astrophysics Data System (ADS)

Kasten, Jeffrey; Klauser, Antoine; Lazeyras, François; Van De Ville, Dimitri

2016-02-01

The notion of non-invasive, high-resolution spatial mapping of metabolite concentrations has long enticed the medical community. While magnetic resonance spectroscopic imaging (MRSI) is capable of achieving the requisite spatio-spectral localization, it has traditionally been encumbered by significant resolution constraints that have thus far undermined its clinical utility. To surpass these obstacles, research efforts have primarily focused on hardware enhancements or the development of accelerated acquisition strategies to improve the experimental sensitivity per unit time. Concomitantly, a number of innovative reconstruction techniques have emerged as alternatives to the standard inverse discrete Fourier transform (DFT). While perhaps lesser known, these latter methods strive to effect commensurate resolution gains by exploiting known properties of the underlying MRSI signal in concert with advanced image and signal processing techniques. This review article aims to aggregate and provide an overview of the past few decades of so-called "superresolution" MRSI reconstruction methodologies, and to introduce readers to current state-of-the-art approaches. A number of perspectives are then offered as to the future of high-resolution MRSI, with a particular focus on translation into clinical settings.

Wavelet methods in multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Helin, T.; Yudytskiy, M.

2013-08-01

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory.

Correction of scatter in megavoltage cone-beam CT

NASA Astrophysics Data System (ADS)

Spies, L.; Ebert, M.; Groh, B. A.; Hesse, B. M.; Bortfeld, T.

2001-03-01

The role of scatter in a cone-beam computed tomography system using the therapeutic beam of a medical linear accelerator and a commercial electronic portal imaging device (EPID) is investigated. A scatter correction method is presented which is based on a superposition of Monte Carlo generated scatter kernels. The kernels are adapted to both the spectral response of the EPID and the dimensions of the phantom being scanned. The method is part of a calibration procedure which converts the measured transmission data acquired for each projection angle into water-equivalent thicknesses. Tomographic reconstruction of the projections then yields an estimate of the electron density distribution of the phantom. It is found that scatter produces cupping artefacts in the reconstructed tomograms. Furthermore, reconstructed electron densities deviate greatly (by about 30%) from their expected values. The scatter correction method removes the cupping artefacts and decreases the deviations from 30% down to about 8%.

Blind beam-hardening correction from Poisson measurements

NASA Astrophysics Data System (ADS)

Gu, Renliang; Dogandžić, Aleksandar

2016-02-01

We develop a sparse image reconstruction method for Poisson-distributed polychromatic X-ray computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. We employ our mass-attenuation spectrum parameterization of the noiseless measurements and express the mass- attenuation spectrum as a linear combination of B-spline basis functions of order one. A block coordinate-descent algorithm is developed for constrained minimization of a penalized Poisson negative log-likelihood (NLL) cost function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and nonnegativity and sparsity of the density map image; the image sparsity is imposed using a convex total-variation (TV) norm penalty term. This algorithm alternates between a Nesterov's proximal-gradient (NPG) step for estimating the density map image and a limited-memory Broyden-Fletcher-Goldfarb-Shanno with box constraints (L-BFGS-B) step for estimating the incident-spectrum parameters. To accelerate convergence of the density- map NPG steps, we apply function restart and a step-size selection scheme that accounts for varying local Lipschitz constants of the Poisson NLL. Real X-ray CT reconstruction examples demonstrate the performance of the proposed scheme.

X-PROP: a fast and robust diffusion-weighted propeller technique.

PubMed

Li, Zhiqiang; Pipe, James G; Lee, Chu-Yu; Debbins, Josef P; Karis, John P; Huo, Donglai

2011-08-01

Diffusion-weighted imaging (DWI) has shown great benefits in clinical MR exams. However, current DWI techniques have shortcomings of sensitivity to distortion or long scan times or combinations of the two. Diffusion-weighted echo-planar imaging (EPI) is fast but suffers from severe geometric distortion. Periodically rotated overlapping parallel lines with enhanced reconstruction diffusion-weighted imaging (PROPELLER DWI) is free of geometric distortion, but the scan time is usually long and imposes high Specific Absorption Rate (SAR) especially at high fields. TurboPROP was proposed to accelerate the scan by combining signal from gradient echoes, but the off-resonance artifacts from gradient echoes can still degrade the image quality. In this study, a new method called X-PROP is presented. Similar to TurboPROP, it uses gradient echoes to reduce the scan time. By separating the gradient and spin echoes into individual blades and removing the off-resonance phase, the off-resonance artifacts in X-PROP are minimized. Special reconstruction processes are applied on these blades to correct for the motion artifacts. In vivo results show its advantages over EPI, PROPELLER DWI, and TurboPROP techniques. Copyright © 2011 Wiley-Liss, Inc.

List-mode reconstruction for the Biograph mCT with physics modeling and event-by-event motion correction

NASA Astrophysics Data System (ADS)

Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

2013-08-01

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction.

List-mode Reconstruction for the Biograph mCT with Physics Modeling and Event-by-Event Motion Correction

PubMed Central

Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

2013-01-01

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32-bit packets, where averaging of lines of response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic assignment of LOR positions (pLOR) that addresses axial and transaxial LOR grouping in 32-bit data. Second, two simplified approaches for 3D TOF scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + time-of-flight (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32-bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction. PMID:23892635

Optical cone beam tomography of Cherenkov-mediated signals for fast 3D dosimetry of x-ray photon beams in water.

PubMed

Glaser, Adam K; Andreozzi, Jacqueline M; Zhang, Rongxiao; Pogue, Brian W; Gladstone, David J

2015-07-01

To test the use of a three-dimensional (3D) optical cone beam computed tomography reconstruction algorithm, for estimation of the imparted 3D dose distribution from megavoltage photon beams in a water tank for quality assurance, by imaging the induced Cherenkov-excited fluorescence (CEF). An intensified charge-coupled device coupled to a standard nontelecentric camera lens was used to tomographically acquire two-dimensional (2D) projection images of CEF from a complex multileaf collimator (MLC) shaped 6 MV linear accelerator x-ray photon beam operating at a dose rate of 600 MU/min. The resulting projections were used to reconstruct the 3D CEF light distribution, a potential surrogate of imparted dose, using a Feldkamp-Davis-Kress cone beam back reconstruction algorithm. Finally, the reconstructed light distributions were compared to the expected dose values from one-dimensional diode scans, 2D film measurements, and the 3D distribution generated from the clinical Varian ECLIPSE treatment planning system using a gamma index analysis. A Monte Carlo derived correction was applied to the Cherenkov reconstructions to account for beam hardening artifacts. 3D light volumes were successfully reconstructed over a 400 × 400 × 350 mm(3) volume at a resolution of 1 mm. The Cherenkov reconstructions showed agreement with all comparative methods and were also able to recover both inter- and intra-MLC leaf leakage. Based upon a 3%/3 mm criterion, the experimental Cherenkov light measurements showed an 83%-99% pass fraction depending on the chosen threshold dose. The results from this study demonstrate the use of optical cone beam computed tomography using CEF for the profiling of the imparted dose distribution from large area megavoltage photon beams in water.

Online monitoring of oil film using electrical capacitance tomography and level set method.

PubMed

Xue, Q; Sun, B Y; Cui, Z Q; Ma, M; Wang, H X

2015-08-01

In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.

Online monitoring of oil film using electrical capacitance tomography and level set method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xue, Q., E-mail: xueqian@tju.edu.cn; Ma, M.; Sun, B. Y.

2015-08-15

In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for onlinemore » monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.« less

Multi-Depth-Map Raytracing for Efficient Large-Scene Reconstruction.

PubMed

Arikan, Murat; Preiner, Reinhold; Wimmer, Michael

2016-02-01

With the enormous advances of the acquisition technology over the last years, fast processing and high-quality visualization of large point clouds have gained increasing attention. Commonly, a mesh surface is reconstructed from the point cloud and a high-resolution texture is generated over the mesh from the images taken at the site to represent surface materials. However, this global reconstruction and texturing approach becomes impractical with increasing data sizes. Recently, due to its potential for scalability and extensibility, a method for texturing a set of depth maps in a preprocessing and stitching them at runtime has been proposed to represent large scenes. However, the rendering performance of this method is strongly dependent on the number of depth maps and their resolution. Moreover, for the proposed scene representation, every single depth map has to be textured by the images, which in practice heavily increases processing costs. In this paper, we present a novel method to break these dependencies by introducing an efficient raytracing of multiple depth maps. In a preprocessing phase, we first generate high-resolution textured depth maps by rendering the input points from image cameras and then perform a graph-cut based optimization to assign a small subset of these points to the images. At runtime, we use the resulting point-to-image assignments (1) to identify for each view ray which depth map contains the closest ray-surface intersection and (2) to efficiently compute this intersection point. The resulting algorithm accelerates both the texturing and the rendering of the depth maps by an order of magnitude.

Vorticity field measurement using digital inline holography

NASA Astrophysics Data System (ADS)

Mallery, Kevin; Hong, Jiarong

2017-11-01

We demonstrate the direct measurement of a 3D vorticity field using digital inline holographic microscopy. Microfiber tracer particles are illuminated with a 532 nm continuous diode laser and imaged using a single CCD camera. The recorded holographic images are processed using a GPU-accelerated inverse problem approach to reconstruct the 3D structure of each microfiber in the imaged volume. The translation and rotation of each microfiber are measured using a time-resolved image sequence - yielding velocity and vorticity point measurements. The accuracy and limitations of this method are investigated using synthetic holograms. Measurements of solid body rotational flow are used to validate the accuracy of the technique under known flow conditions. The technique is further applied to a practical turbulent flow case for investigating its 3D velocity field and vorticity distribution.

A comparison of five standard methods for evaluating image intensity uniformity in partially parallel imaging MRI

PubMed Central

Goerner, Frank L.; Duong, Timothy; Stafford, R. Jason; Clarke, Geoffrey D.

2013-01-01

Purpose: To investigate the utility of five different standard measurement methods for determining image uniformity for partially parallel imaging (PPI) acquisitions in terms of consistency across a variety of pulse sequences and reconstruction strategies. Methods: Images were produced with a phantom using a 12-channel head matrix coil in a 3T MRI system (TIM TRIO, Siemens Medical Solutions, Erlangen, Germany). Images produced using echo-planar, fast spin echo, gradient echo, and balanced steady state free precession pulse sequences were evaluated. Two different PPI reconstruction methods were investigated, generalized autocalibrating partially parallel acquisition algorithm (GRAPPA) and modified sensitivity-encoding (mSENSE) with acceleration factors (R) of 2, 3, and 4. Additionally images were acquired with conventional, two-dimensional Fourier imaging methods (R = 1). Five measurement methods of uniformity, recommended by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) were considered. The methods investigated were (1) an ACR method and a (2) NEMA method for calculating the peak deviation nonuniformity, (3) a modification of a NEMA method used to produce a gray scale uniformity map, (4) determining the normalized absolute average deviation uniformity, and (5) a NEMA method that focused on 17 areas of the image to measure uniformity. Changes in uniformity as a function of reconstruction method at the same R-value were also investigated. Two-way analysis of variance (ANOVA) was used to determine whether R-value or reconstruction method had a greater influence on signal intensity uniformity measurements for partially parallel MRI. Results: Two of the methods studied had consistently negative slopes when signal intensity uniformity was plotted against R-value. The results obtained comparing mSENSE against GRAPPA found no consistent difference between GRAPPA and mSENSE with regard to signal intensity uniformity. The results of the two-way ANOVA analysis suggest that R-value and pulse sequence type produce the largest influences on uniformity and PPI reconstruction method had relatively little effect. Conclusions: Two of the methods of measuring signal intensity uniformity, described by the (NEMA) MRI standards, consistently indicated a decrease in uniformity with an increase in R-value. Other methods investigated did not demonstrate consistent results for evaluating signal uniformity in MR images obtained by partially parallel methods. However, because the spatial distribution of noise affects uniformity, it is recommended that additional uniformity quality metrics be investigated for partially parallel MR images. PMID:23927345

Breast ultrasound computed tomography using waveform inversion with source encoding

NASA Astrophysics Data System (ADS)

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A.

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

TomoBank: a tomographic data repository for computational x-ray science

NASA Astrophysics Data System (ADS)

De Carlo, Francesco; Gürsoy, Doğa; Ching, Daniel J.; Joost Batenburg, K.; Ludwig, Wolfgang; Mancini, Lucia; Marone, Federica; Mokso, Rajmund; Pelt, Daniël M.; Sijbers, Jan; Rivers, Mark

2018-03-01

There is a widening gap between the fast advancement of computational methods for tomographic reconstruction and their successful implementation in production software at various synchrotron facilities. This is due in part to the lack of readily available instrument datasets and phantoms representative of real materials for validation and comparison of new numerical methods. Recent advancements in detector technology have made sub-second and multi-energy tomographic data collection possible (Gibbs et al 2015 Sci. Rep. 5 11824), but have also increased the demand to develop new reconstruction methods able to handle in situ (Pelt and Batenburg 2013 IEEE Trans. Image Process. 22 5238-51) and dynamic systems (Mohan et al 2015 IEEE Trans. Comput. Imaging 1 96-111) that can be quickly incorporated in beamline production software (Gürsoy et al 2014 J. Synchrotron Radiat. 21 1188-93). The x-ray tomography data bank, tomoBank, provides a repository of experimental and simulated datasets with the aim to foster collaboration among computational scientists, beamline scientists, and experimentalists and to accelerate the development and implementation of tomographic reconstruction methods for synchrotron facility production software by providing easy access to challenging datasets and their descriptors.

GPU-based Branchless Distance-Driven Projection and Backprojection

PubMed Central

Liu, Rui; Fu, Lin; De Man, Bruno; Yu, Hengyong

2017-01-01

Projection and backprojection operations are essential in a variety of image reconstruction and physical correction algorithms in CT. The distance-driven (DD) projection and backprojection are widely used for their highly sequential memory access pattern and low arithmetic cost. However, a typical DD implementation has an inner loop that adjusts the calculation depending on the relative position between voxel and detector cell boundaries. The irregularity of the branch behavior makes it inefficient to be implemented on massively parallel computing devices such as graphics processing units (GPUs). Such irregular branch behaviors can be eliminated by factorizing the DD operation as three branchless steps: integration, linear interpolation, and differentiation, all of which are highly amenable to massive vectorization. In this paper, we implement and evaluate a highly parallel branchless DD algorithm for 3D cone beam CT. The algorithm utilizes the texture memory and hardware interpolation on GPUs to achieve fast computational speed. The developed branchless DD algorithm achieved 137-fold speedup for forward projection and 188-fold speedup for backprojection relative to a single-thread CPU implementation. Compared with a state-of-the-art 32-thread CPU implementation, the proposed branchless DD achieved 8-fold acceleration for forward projection and 10-fold acceleration for backprojection. GPU based branchless DD method was evaluated by iterative reconstruction algorithms with both simulation and real datasets. It obtained visually identical images as the CPU reference algorithm. PMID:29333480

GPU-based Branchless Distance-Driven Projection and Backprojection.

PubMed

Liu, Rui; Fu, Lin; De Man, Bruno; Yu, Hengyong

2017-12-01

Projection and backprojection operations are essential in a variety of image reconstruction and physical correction algorithms in CT. The distance-driven (DD) projection and backprojection are widely used for their highly sequential memory access pattern and low arithmetic cost. However, a typical DD implementation has an inner loop that adjusts the calculation depending on the relative position between voxel and detector cell boundaries. The irregularity of the branch behavior makes it inefficient to be implemented on massively parallel computing devices such as graphics processing units (GPUs). Such irregular branch behaviors can be eliminated by factorizing the DD operation as three branchless steps: integration, linear interpolation, and differentiation, all of which are highly amenable to massive vectorization. In this paper, we implement and evaluate a highly parallel branchless DD algorithm for 3D cone beam CT. The algorithm utilizes the texture memory and hardware interpolation on GPUs to achieve fast computational speed. The developed branchless DD algorithm achieved 137-fold speedup for forward projection and 188-fold speedup for backprojection relative to a single-thread CPU implementation. Compared with a state-of-the-art 32-thread CPU implementation, the proposed branchless DD achieved 8-fold acceleration for forward projection and 10-fold acceleration for backprojection. GPU based branchless DD method was evaluated by iterative reconstruction algorithms with both simulation and real datasets. It obtained visually identical images as the CPU reference algorithm.

A PET system based on 2-18FDG production with a low energy electrostatic proton accelerator and a dual headed PET scanner.

PubMed

Sandell, A; Ohlsson, T; Erlandsson, K; Hellborg, R; Strand, S E

1992-01-01

We have developed a comparatively inexpensive PET system, based on a rotating scanner with two scintillation camera heads, and a nearby low energy electrostatic proton accelerator for production of short-lived radionuclides. Using a 6 MeV proton beam of 5 microA, and by optimization of the target geometry for the 18O(p,n)18F reaction, 750 MBq of 2-18FDG can be obtained. The PET scanner shows a spatial resolution of 6 mm (FWHM) and a sensitivity of 80 s-1kBq-1ml-1 (3 kcps/microCi/ml). Various corrections are included in the imaging process, to compensate for spatial and temporal response variations in the detector system. Both filtered backprojection and iterative reconstruction methods are employed. Clinical studies have been performed with acquisition times of 30-40 min. The system will be used for clinical experimental research with short- as well as long-lived positron emitters. Also the possibility of true 3D reconstruction is under evaluation.

Accelerated high-resolution photoacoustic tomography via compressed sensing

NASA Astrophysics Data System (ADS)

Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward

2016-12-01

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.

Online Kidney Position Verification Using Non-Contrast Radiographs on a Linear Accelerator with on Board KV X-Ray Imaging Capability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willis, David J.; Kron, Tomas; Hubbard, Patricia

2009-01-01

The kidneys are dose-limiting organs in abdominal radiotherapy. Kilovoltage (kV) radiographs can be acquired using on-board imager (OBI)-equipped linear accelerators with better soft tissue contrast and lower radiation doses than conventional portal imaging. A feasibility study was conducted to test the suitability of anterior-posterior (AP) non-contrast kV radiographs acquired at treatment time for online kidney position verification. Anthropomorphic phantoms were used to evaluate image quality and radiation dose. Institutional Review Board approval was given for a pilot study that enrolled 5 adults and 5 children. Customized digitally reconstructed radiographs (DRRs) were generated to provide a priori information on kidney shapemore » and position. Radiotherapy treatment staff performed online evaluation of kidney visibility on OBI radiographs. Kidney dose measured in a pediatric anthropomorphic phantom was 0.1 cGy for kV imaging and 1.7 cGy for MV imaging. Kidneys were rated as well visualized in 60% of patients (90% confidence interval, 34-81%). The likelihood of visualization appears to be influenced by the relative AP separation of the abdomen and kidneys, the axial profile of the kidneys, and their relative contrast with surrounding structures. Online verification of kidney position using AP non-contrast kV radiographs on an OBI-equipped linear accelerator appears feasible for patients with suitable abdominal anatomy. Kidney position information provided is limited to 2-dimensional 'snapshots,' but this is adequate in some clinical situations and potentially advantageous in respiratory-correlated treatments. Successful clinical implementation requires customized partial DRRs, appropriate imaging parameters, and credentialing of treatment staff.« less

Accelerating cross-validation with total variation and its application to super-resolution imaging

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Ikeda, Shiro; Akiyama, Kazunori; Kabashima, Yoshiyuki

2017-12-01

We develop an approximation formula for the cross-validation error (CVE) of a sparse linear regression penalized by ℓ_1-norm and total variation terms, which is based on a perturbative expansion utilizing the largeness of both the data dimensionality and the model. The developed formula allows us to reduce the necessary computational cost of the CVE evaluation significantly. The practicality of the formula is tested through application to simulated black-hole image reconstruction on the event-horizon scale with super resolution. The results demonstrate that our approximation reproduces the CVE values obtained via literally conducted cross-validation with reasonably good precision.

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS)

NASA Astrophysics Data System (ADS)

Park, Suhyung; Park, Jaeseok

2015-05-01

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS).

PubMed

Park, Suhyung; Park, Jaeseok

2015-05-07

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

SC-GRAPPA: Self-constraint noniterative GRAPPA reconstruction with closed-form solution.

PubMed

Ding, Yu; Xue, Hui; Ahmad, Rizwan; Ting, Samuel T; Simonetti, Orlando P

2012-12-01

Parallel MRI (pMRI) reconstruction techniques are commonly used to reduce scan time by undersampling the k-space data. GRAPPA, a k-space based pMRI technique, is widely used clinically because of its robustness. In GRAPPA, the missing k-space data are estimated by solving a set of linear equations; however, this set of equations does not take advantage of the correlations within the missing k-space data. All k-space data in a neighborhood acquired from a phased-array coil are correlated. The correlation can be estimated easily as a self-constraint condition, and formulated as an extra set of linear equations to improve the performance of GRAPPA. The authors propose a modified k-space based pMRI technique called self-constraint GRAPPA (SC-GRAPPA) which combines the linear equations of GRAPPA with these extra equations to solve for the missing k-space data. Since SC-GRAPPA utilizes a least-squares solution of the linear equations, it has a closed-form solution that does not require an iterative solver. The SC-GRAPPA equation was derived by incorporating GRAPPA as a prior estimate. SC-GRAPPA was tested in a uniform phantom and two normal volunteers. MR real-time cardiac cine images with acceleration rate 5 and 6 were reconstructed using GRAPPA and SC-GRAPPA. SC-GRAPPA showed a significantly lower artifact level, and a greater than 10% overall signal-to-noise ratio (SNR) gain over GRAPPA, with more significant SNR gain observed in low-SNR regions of the images. SC-GRAPPA offers improved pMRI reconstruction, and is expected to benefit clinical imaging applications in the future.

X-ray coherent scattering tomography of textured material (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhu, Zheyuan; Pang, Shuo

2017-05-01

Small-angle X-ray scattering (SAXS) measures the signature of angular-dependent coherently scattered X-rays, which contains richer information in material composition and structure compared to conventional absorption-based computed tomography. SAXS image reconstruction method of a 2 or 3 dimensional object based on computed tomography, termed as coherent scattering computed tomography (CSCT), enables the detection of spatially-resolved, material-specific isotropic scattering signature inside an extended object, and provides improved contrast for medical diagnosis, security screening, and material characterization applications. However, traditional CSCT methods assumes materials are fine powders or amorphous, and possess isotropic scattering profiles, which is not generally true for all materials. Anisotropic scatters cannot be captured using conventional CSCT method and result in reconstruction errors. To obtain correct information from the sample, we designed new imaging strategy which incorporates extra degree of detector motion into X-ray scattering tomography for the detection of anisotropic scattered photons from a series of two-dimensional intensity measurements. Using a table-top, narrow-band X-ray source and a panel detector, we demonstrate the anisotropic scattering profile captured from an extended object and the reconstruction of a three-dimensional object. For materials possessing a well-organized crystalline structure with certain symmetry, the scatter texture is more predictable. We will also discuss the compressive schemes and implementation of data acquisition to improve the collection efficiency and accelerate the imaging process.

Optimal resolution in maximum entropy image reconstruction from projections with multigrid acceleration

NASA Technical Reports Server (NTRS)

Limber, Mark A.; Manteuffel, Thomas A.; Mccormick, Stephen F.; Sholl, David S.

1993-01-01

We consider the problem of image reconstruction from a finite number of projections over the space L(sup 1)(Omega), where Omega is a compact subset of the set of Real numbers (exp 2). We prove that, given a discretization of the projection space, the function that generates the correct projection data and maximizes the Boltzmann-Shannon entropy is piecewise constant on a certain discretization of Omega, which we call the 'optimal grid'. It is on this grid that one obtains the maximum resolution given the problem setup. The size of this grid grows very quickly as the number of projections and number of cells per projection grow, indicating fast computational methods are essential to make its use feasible. We use a Fenchel duality formulation of the problem to keep the number of variables small while still using the optimal discretization, and propose a multilevel scheme to improve convergence of a simple cyclic maximization scheme applied to the dual problem.

Anatomic ACL reconstruction: does the platelet-rich plasma accelerate tendon healing?

PubMed

Silva, Alcindo; Sampaio, Ricardo

2009-06-01

Recently, the use of hamstring tendons in anterior cruciate ligament repair has been increasing. However, tendon-to-bone healing occurs slowly, which can be a problem to an early return to sport activities. The use of growth factors from platelets seems to improve tissue healing. We enrolled 40 patients in a prospective study that were submitted to an anatomic reconstruction of the anterior cruciate ligament. Patients were sequentially enrolled into four groups: group A without platelet-rich plasma (PRP); group B with PRP in femoral tunnels at the end of surgery; group C with PRP in femoral tunnels at the end of surgery and intra-articular at 2- and 4 weeks after surgery; group D with PRP activated with thrombin in the femoral tunnels. All patients underwent magnetic resonance imaging of the knee 3 months after surgery to evaluate the signal intensity of the fibrous interzone (FIZ) in the femoral tunnels. We did not find any difference among the groups when comparing the signal intensity of the FIZ on magnetic resonance imaging.

Geometric artifacts reduction for cone-beam CT via L0-norm minimization without dedicated phantoms.

PubMed

Gong, Changcheng; Cai, Yufang; Zeng, Li

2018-01-01

For cone-beam computed tomography (CBCT), transversal shifts of the rotation center exist inevitably, which will result in geometric artifacts in CT images. In this work, we propose a novel geometric calibration method for CBCT, which can also be used in micro-CT. The symmetry property of the sinogram is used for the first calibration, and then L0-norm of the gradient image from the reconstructed image is used as the cost function to be minimized for the second calibration. An iterative search method is adopted to pursue the local minimum of the L0-norm minimization problem. The transversal shift value is updated with affirmatory step size within a search range determined by the first calibration. In addition, graphic processing unit (GPU)-based FDK algorithm and acceleration techniques are designed to accelerate the calibration process of the presented new method. In simulation experiments, the mean absolute difference (MAD) and the standard deviation (SD) of the transversal shift value were less than 0.2 pixels between the noise-free and noisy projection images, which indicated highly accurate calibration applying the new calibration method. In real data experiments, the smaller entropies of the corrected images also indicated that higher resolution image was acquired using the corrected projection data and the textures were well protected. Study results also support the feasibility of applying the proposed method to other imaging modalities.

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Danny; Pollock, Sean; Keall, Paul, E-mail: paul.keall@sydney.edu.au

2016-05-15

Purpose: The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale)more » respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. Conclusions: This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.« less

Preliminary study on X-ray fluorescence computed tomography imaging of gold nanoparticles: Acceleration of data acquisition by multiple pinholes scheme

NASA Astrophysics Data System (ADS)

Sasaya, Tenta; Sunaguchi, Naoki; Seo, Seung-Jum; Hyodo, Kazuyuki; Zeniya, Tsutomu; Kim, Jong-Ki; Yuasa, Tetsuya

2018-04-01

Gold nanoparticles (GNPs) have recently attracted attention in nanomedicine as novel contrast agents for cancer imaging. A decisive tomographic imaging technique has not yet been established to depict the 3-D distribution of GNPs in an object. An imaging technique known as pinhole-based X-ray fluorescence computed tomography (XFCT) is a promising method that can be used to reconstruct the distribution of GNPs from the X-ray fluorescence emitted by GNPs. We address the acceleration of data acquisition in pinhole-based XFCT for preclinical use using a multiple pinhole scheme. In this scheme, multiple projections are simultaneously acquired through a multi-pinhole collimator with a 2-D detector and full-field volumetric beam to enhance the signal-to-noise ratio of the projections; this enables fast data acquisition. To demonstrate the efficacy of this method, we performed an imaging experiment using a physical phantom with an actual multi-pinhole XFCT system that was constructed using the beamline AR-NE7A at KEK. The preliminary study showed that the multi-pinhole XFCT achieved a data acquisition time of 20 min at a theoretical detection limit of approximately 0.1 Au mg/ml and at a spatial resolution of 0.4 mm.

Golden-ratio rotated stack-of-stars acquisition for improved volumetric MRI.

PubMed

Zhou, Ziwu; Han, Fei; Yan, Lirong; Wang, Danny J J; Hu, Peng

2017-12-01

To develop and evaluate an improved stack-of-stars radial sampling strategy for reducing streaking artifacts. The conventional stack-of-stars sampling strategy collects the same radial angle for every partition (slice) encoding. In an undersampled acquisition, such an aligned acquisition generates coherent aliasing patterns and introduces strong streaking artifacts. We show that by rotating the radial spokes in a golden-angle manner along the partition-encoding direction, the aliasing pattern is modified, resulting in improved image quality for gridding and more advanced reconstruction methods. Computer simulations were performed and phantom as well as in vivo images for three different applications were acquired. Simulation, phantom, and in vivo experiments confirmed that the proposed method was able to generate images with less streaking artifact and sharper structures based on undersampled acquisitions in comparison with the conventional aligned approach at the same acceleration factors. By combining parallel imaging and compressed sensing in the reconstruction, streaking artifacts were mostly removed with improved delineation of fine structures using the proposed strategy. We present a simple method to reduce streaking artifacts and improve image quality in 3D stack-of-stars acquisitions by re-arranging the radial spoke angles in the 3D partition direction, which can be used for rapid volumetric imaging. Magn Reson Med 78:2290-2298, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

De-noising of 3D multiple-coil MR images using modified LMMSE estimator.

PubMed

Yaghoobi, Nima; Hasanzadeh, Reza P R

2018-06-20

De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones. Copyright © 2018. Published by Elsevier Inc.

s-SMOOTH: Sparsity and Smoothness Enhanced EEG Brain Tomography

PubMed Central

Li, Ying; Qin, Jing; Hsin, Yue-Loong; Osher, Stanley; Liu, Wentai

2016-01-01

EEG source imaging enables us to reconstruct current density in the brain from the electrical measurements with excellent temporal resolution (~ ms). The corresponding EEG inverse problem is an ill-posed one that has infinitely many solutions. This is due to the fact that the number of EEG sensors is usually much smaller than that of the potential dipole locations, as well as noise contamination in the recorded signals. To obtain a unique solution, regularizations can be incorporated to impose additional constraints on the solution. An appropriate choice of regularization is critically important for the reconstruction accuracy of a brain image. In this paper, we propose a novel Sparsity and SMOOthness enhanced brain TomograpHy (s-SMOOTH) method to improve the reconstruction accuracy by integrating two recently proposed regularization techniques: Total Generalized Variation (TGV) regularization and ℓ1−2 regularization. TGV is able to preserve the source edge and recover the spatial distribution of the source intensity with high accuracy. Compared to the relevant total variation (TV) regularization, TGV enhances the smoothness of the image and reduces staircasing artifacts. The traditional TGV defined on a 2D image has been widely used in the image processing field. In order to handle 3D EEG source images, we propose a voxel-based Total Generalized Variation (vTGV) regularization that extends the definition of second-order TGV from 2D planar images to 3D irregular surfaces such as cortex surface. In addition, the ℓ1−2 regularization is utilized to promote sparsity on the current density itself. We demonstrate that ℓ1−2 regularization is able to enhance sparsity and accelerate computations than ℓ1 regularization. The proposed model is solved by an efficient and robust algorithm based on the difference of convex functions algorithm (DCA) and the alternating direction method of multipliers (ADMM). Numerical experiments using synthetic data demonstrate the advantages of the proposed method over other state-of-the-art methods in terms of total reconstruction accuracy, localization accuracy and focalization degree. The application to the source localization of event-related potential data further demonstrates the performance of the proposed method in real-world scenarios. PMID:27965529

The Influence of Knee Flexion Angle for Graft Fixation on Rotational Knee Stability During Anterior Cruciate Ligament Reconstruction: A Biomechanical Study.

PubMed

Debandi, Aníbal; Maeyama, Akira; Hoshino, Yuichi; Asai, Shigehiro; Goto, Bunsei; Smolinski, Patrick; Fu, Freddie H

2016-11-01

To evaluate the effect of knee flexion angle for hamstring graft fixation, full extension (FE), or 30°, on acceleration of the knee motion during pivot-shift testing after either anatomic or nonanatomic anterior cruciate ligament (ACL) reconstruction using triaxial accelerometry. Two types of ACL reconstructions (anatomic and nonanatomic) using 2 different angles of knee flexion during graft fixation (FE and 30°) were performed on 12 fresh-frozen human knees making 4 groups: anatomic-FE, anatomic-30°, nonanatomic-FE, and nonanatomic-30°. Manual pivot-shift testing was performed at ACL-intact, ACL-deficient, and ACL-reconstructed conditions. Three-dimensional acceleration of knee motion was recorded using a triaxial accelerometer. The anatomic-30° group showed the smallest overall magnitude of acceleration among the ACL-reconstructed groups (P = .0039). There were no significant differences among the anatomic-FE group, the nonanatomic-FE group, and the nonantomic-30° group (anatomic-FE vs nonanatomic-FE, P = .1093; anatomic-FE vs nonanatomic-30°, P = .8728; and nonanatomic-FE vs nonanatomic-30°, P = .1093). After ACL transection, acceleration was reduced by ACL reconstruction with the exception of the nonanatomic-FE group that did not show a significant difference when compared with the ACL-deficient (P = .4537). The anatomic ACL reconstruction with the graft fixed at 30° of knee flexion better restored rotational knee stability compared with FE. An ACL graft fixed with the knee at FE in anatomic position did not show a significant difference compared with the nonanatomic ACL reconstructions. Knee flexion angle at the time of graft fixation for ACL reconstruction can be considered to maximize the rotational knee stability. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

An infrared-visible image fusion scheme based on NSCT and compressed sensing

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Maldague, Xavier

2015-05-01

Image fusion, as a research hot point nowadays in the field of infrared computer vision, has been developed utilizing different varieties of methods. Traditional image fusion algorithms are inclined to bring problems, such as data storage shortage and computational complexity increase, etc. Compressed sensing (CS) uses sparse sampling without knowing the priori knowledge and greatly reconstructs the image, which reduces the cost and complexity of image processing. In this paper, an advanced compressed sensing image fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. NSCT provides better sparsity than the wavelet transform in image representation. Throughout the NSCT decomposition, the low-frequency and high-frequency coefficients can be obtained respectively. For the fusion processing of low-frequency coefficients of infrared and visible images , the adaptive regional energy weighting rule is utilized. Thus only the high-frequency coefficients are specially measured. Here we use sparse representation and random projection to obtain the required values of high-frequency coefficients, afterwards, the coefficients of each image block can be fused via the absolute maximum selection rule and/or the regional standard deviation rule. In the reconstruction of the compressive sampling results, a gradient-based iterative algorithm and the total variation (TV) method are employed to recover the high-frequency coefficients. Eventually, the fused image is recovered by inverse NSCT. Both the visual effects and the numerical computation results after experiments indicate that the presented approach achieves much higher quality of image fusion, accelerates the calculations, enhances various targets and extracts more useful information.

GPU-accelerated Lattice Boltzmann method for anatomical extraction in patient-specific computational hemodynamics

NASA Astrophysics Data System (ADS)

Yu, H.; Wang, Z.; Zhang, C.; Chen, N.; Zhao, Y.; Sawchuk, A. P.; Dalsing, M. C.; Teague, S. D.; Cheng, Y.

2014-11-01

Existing research of patient-specific computational hemodynamics (PSCH) heavily relies on software for anatomical extraction of blood arteries. Data reconstruction and mesh generation have to be done using existing commercial software due to the gap between medical image processing and CFD, which increases computation burden and introduces inaccuracy during data transformation thus limits the medical applications of PSCH. We use lattice Boltzmann method (LBM) to solve the level-set equation over an Eulerian distance field and implicitly and dynamically segment the artery surfaces from radiological CT/MRI imaging data. The segments seamlessly feed to the LBM based CFD computation of PSCH thus explicit mesh construction and extra data management are avoided. The LBM is ideally suited for GPU (graphic processing unit)-based parallel computing. The parallel acceleration over GPU achieves excellent performance in PSCH computation. An application study will be presented which segments an aortic artery from a chest CT dataset and models PSCH of the segmented artery.

Effects of a platelet gel on early graft revascularization after anterior cruciate ligament reconstruction: a prospective, randomized, double-blind, clinical trial.

PubMed

Vogrin, M; Rupreht, M; Dinevski, D; Hašpl, M; Kuhta, M; Jevsek, M; Knežević, M; Rožman, P

2010-01-01

Slow graft healing in bone tunnels and a slow graft ligamentization process after anterior cruciate ligament (ACL) reconstruction are some of the reasons for prolonged rehabilitation. The purpose of this study was to determine if the use of platelet gel (PG) accelerates early graft revascularization after ACL reconstruction. PG was produced from autologous platelet-rich plasma and applied locally. We quantitatively evaluated the revascularization process in the osteoligamentous interface zone in the bone tunnels and in the intra-articular part of the graft by means of contrast-enhanced magnetic resonance imaging (MRI). After 4-6 weeks, the PG-treated group demonstrated a significantly higher level of vascularization in the osteoligamentous interface (0.33 ± 0.09) than the control group (0.16 ± 0.09, p < 0.001). In the intra-articular part of the graft, we found no evidence of revascularization in either group. Locally applied PG enhanced early revascularization of the graft in the osteoligamentous interface zone after ACL reconstruction. Copyright © 2010 S. Karger AG, Basel.

Fast carotid artery MR angiography with compressed sensing based three-dimensional time-of-flight sequence.

PubMed

Li, Bo; Li, Hao; Dong, Li; Huang, Guofu

2017-11-01

In this study, we sought to investigate the feasibility of fast carotid artery MR angiography (MRA) by combining three-dimensional time-of-flight (3D TOF) with compressed sensing method (CS-3D TOF). A pseudo-sequential phase encoding order was developed for CS-3D TOF to generate hyper-intense vessel and suppress background tissues in under-sampled 3D k-space. Seven healthy volunteers and one patient with carotid artery stenosis were recruited for this study. Five sequential CS-3D TOF scans were implemented at 1, 2, 3, 4 and 5-fold acceleration factors for carotid artery MRA. Blood signal-to-tissue ratio (BTR) values for fully-sampled and under-sampled acquisitions were calculated and compared in seven subjects. Blood area (BA) was measured and compared between fully sampled acquisition and each under-sampled one. There were no significant differences between the fully-sampled dataset and each under-sampled in BTR comparisons (P>0.05 for all comparisons). The carotid vessel BAs measured from the images of CS-3D TOF sequences with 2, 3, 4 and 5-fold acceleration scans were all highly correlated with that of the fully-sampled acquisition. The contrast between blood vessels and background tissues of the images at 2 to 5-fold acceleration is comparable to that of fully sampled images. The images at 2× to 5× exhibit the comparable lumen definition to the corresponding images at 1×. By combining the pseudo-sequential phase encoding order, CS reconstruction, and 3D TOF sequence, this technique provides excellent visualizations for carotid vessel and calcifications in a short scan time. It has the potential to be integrated into current multiple blood contrast imaging protocol. Copyright © 2017. Published by Elsevier Inc.

Beyond filtered backprojection: A reconstruction software package for ion beam microtomography data

NASA Astrophysics Data System (ADS)

Habchi, C.; Gordillo, N.; Bourret, S.; Barberet, Ph.; Jovet, C.; Moretto, Ph.; Seznec, H.

2013-01-01

A new version of the TomoRebuild data reduction software package is presented, for the reconstruction of scanning transmission ion microscopy tomography (STIMT) and particle induced X-ray emission tomography (PIXET) images. First, we present a state of the art of the reconstruction codes available for ion beam microtomography. The algorithm proposed here brings several advantages. It is a portable, multi-platform code, designed in C++ with well-separated classes for easier use and evolution. Data reduction is separated in different steps and the intermediate results may be checked if necessary. Although no additional graphic library or numerical tool is required to run the program as a command line, a user friendly interface was designed in Java, as an ImageJ plugin. All experimental and reconstruction parameters may be entered either through this plugin or directly in text format files. A simple standard format is proposed for the input of experimental data. Optional graphic applications using the ROOT interface may be used separately to display and fit energy spectra. Regarding the reconstruction process, the filtered backprojection (FBP) algorithm, already present in the previous version of the code, was optimized so that it is about 10 times as fast. In addition, Maximum Likelihood Expectation Maximization (MLEM) and its accelerated version Ordered Subsets Expectation Maximization (OSEM) algorithms were implemented. A detailed user guide in English is available. A reconstruction example of experimental data from a biological sample is given. It shows the capability of the code to reduce noise in the sinograms and to deal with incomplete data, which puts a new perspective on tomography using low number of projections or limited angle.

Image-based reconstruction of the Newtonian dynamics of solar coronal ejecta

NASA Astrophysics Data System (ADS)

Uritsky, Vadim M.; Thompson, Barbara J.

2016-10-01

We present a new methodology for analyzing rising and falling dynamics of unstable coronal material as represented by high-cadence SDO AIA images. The technique involves an adaptive spatiotemporal tracking of propagating intensity gradients and their characterization in terms of time-evolving areas swept out by the position vector originated from the Sun disk center. The measured values of the areal velocity and acceleration are used to obtain quantitative information on the angular momentum and acceleration along the paths of the rising and falling coronal plasma. In the absence of other forces, solar gravitation results in purely ballistic motions consistent with the Kepler's second law; non-central forces such as the Lorentz force introduce non-zero torques resulting in more complex motions. The developed algorithms enable direct evaluation of the line-of-sight component of the net torque applied to a unit mass of the ejected coronal material which is proportional to the image-plane projection of the observed areal acceleration. The current implementation of the method cannot reliably distinguish torque modulations caused by the coronal force field from those imposed by abrupt changes of plasma mass density and nontrivial projection effects. However, it can provide valid observational constraints on the evolution of large-scale unstable magnetic topologies driving major solar-coronal eruptions as demonstrated in the related talk by B. Thompson et al.

Adapted random sampling patterns for accelerated MRI.

PubMed

Knoll, Florian; Clason, Christian; Diwoky, Clemens; Stollberger, Rudolf

2011-02-01

Variable density random sampling patterns have recently become increasingly popular for accelerated imaging strategies, as they lead to incoherent aliasing artifacts. However, the design of these sampling patterns is still an open problem. Current strategies use model assumptions like polynomials of different order to generate a probability density function that is then used to generate the sampling pattern. This approach relies on the optimization of design parameters which is very time consuming and therefore impractical for daily clinical use. This work presents a new approach that generates sampling patterns by making use of power spectra of existing reference data sets and hence requires neither parameter tuning nor an a priori mathematical model of the density of sampling points. The approach is validated with downsampling experiments, as well as with accelerated in vivo measurements. The proposed approach is compared with established sampling patterns, and the generalization potential is tested by using a range of reference images. Quantitative evaluation is performed for the downsampling experiments using RMS differences to the original, fully sampled data set. Our results demonstrate that the image quality of the method presented in this paper is comparable to that of an established model-based strategy when optimization of the model parameter is carried out and yields superior results to non-optimized model parameters. However, no random sampling pattern showed superior performance when compared to conventional Cartesian subsampling for the considered reconstruction strategy.

Fast Fourier single-pixel imaging via binary illumination.

PubMed

Zhang, Zibang; Wang, Xueying; Zheng, Guoan; Zhong, Jingang

2017-09-20

Fourier single-pixel imaging (FSI) employs Fourier basis patterns for encoding spatial information and is capable of reconstructing high-quality two-dimensional and three-dimensional images. Fourier-domain sparsity in natural scenes allows FSI to recover sharp images from undersampled data. The original FSI demonstration, however, requires grayscale Fourier basis patterns for illumination. This requirement imposes a limitation on the imaging speed as digital micro-mirror devices (DMDs) generate grayscale patterns at a low refreshing rate. In this paper, we report a new strategy to increase the speed of FSI by two orders of magnitude. In this strategy, we binarize the Fourier basis patterns based on upsampling and error diffusion dithering. We demonstrate a 20,000 Hz projection rate using a DMD and capture 256-by-256-pixel dynamic scenes at a speed of 10 frames per second. The reported technique substantially accelerates image acquisition speed of FSI. It may find broad imaging applications at wavebands that are not accessible using conventional two-dimensional image sensors.

Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction

NASA Astrophysics Data System (ADS)

Hollingsworth, Kieren Grant

2015-11-01

MRI is often the most sensitive or appropriate technique for important measurements in clinical diagnosis and research, but lengthy acquisition times limit its use due to cost and considerations of patient comfort and compliance. Once an image field of view and resolution is chosen, the minimum scan acquisition time is normally fixed by the amount of raw data that must be acquired to meet the Nyquist criteria. Recently, there has been research interest in using the theory of compressed sensing (CS) in MR imaging to reduce scan acquisition times. The theory argues that if our target MR image is sparse, having signal information in only a small proportion of pixels (like an angiogram), or if the image can be mathematically transformed to be sparse then it is possible to use that sparsity to recover a high definition image from substantially less acquired data. This review starts by considering methods of k-space undersampling which have already been incorporated into routine clinical imaging (partial Fourier imaging and parallel imaging), and then explains the basis of using compressed sensing in MRI. The practical considerations of applying CS to MRI acquisitions are discussed, such as designing k-space undersampling schemes, optimizing adjustable parameters in reconstructions and exploiting the power of combined compressed sensing and parallel imaging (CS-PI). A selection of clinical applications that have used CS and CS-PI prospectively are considered. The review concludes by signposting other imaging acceleration techniques under present development before concluding with a consideration of the potential impact and obstacles to bringing compressed sensing into routine use in clinical MRI.

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

PubMed

Wang, Haoyu; Miao, Yanwei; Zhou, Kun; Yu, Yanming; Bao, Shanglian; He, Qiang; Dai, Yongming; Xuan, Stephanie Y; Tarabishy, Bisher; Ye, Yongquan; Hu, Jiani

2010-09-01

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Direct Comparison of Respiration-Correlated Four-Dimensional Magnetic Resonance Imaging Reconstructed Using Concurrent Internal Navigator and External Bellows.

PubMed

Li, Guang; Wei, Jie; Olek, Devin; Kadbi, Mo; Tyagi, Neelam; Zakian, Kristen; Mechalakos, James; Deasy, Joseph O; Hunt, Margie

2017-03-01

To compare the image quality of amplitude-binned 4-dimensional magnetic resonance imaging (4DMRI) reconstructed using 2 concurrent respiratory (navigator and bellows) waveforms. A prospective, respiratory-correlated 4DMRI scanning program was used to acquire T2-weighted single-breath 4DMRI images with internal navigator and external bellows. After a 10-second training waveform of a surrogate signal, 2-dimensional MRI acquisition was triggered at a level (bin) and anatomic location (slice) until the bin-slice table was completed for 4DMRI reconstruction. The bellows signal was always collected, even when the navigator trigger was used, to retrospectively reconstruct a bellows-rebinned 4DMRI. Ten volunteers participated in this institutional review board-approved 4DMRI study. Four scans were acquired for each subject, including coronal and sagittal scans triggered by either navigator or bellows, and 6 4DMRI images (navigator-triggered, bellows-rebinned, and bellows-triggered) were reconstructed. The simultaneously acquired waveforms and resulting 4DMRI quality were compared using signal correlation, bin/phase shift, and binning motion artifacts. The consecutive bellows-triggered 4DMRI scan was used for indirect comparison. Correlation coefficients between the navigator and bellows signals were found to be patient-specific and inhalation-/exhalation-dependent, ranging from 0.1 to 0.9 because of breathing irregularities (>50% scans) and commonly observed bin/phase shifts (-1.1 ± 0.6 bin) in both 1-dimensional waveforms and diaphragm motion extracted from 4D images. Navigator-triggered 4DMRI contained many fewer binning motion artifacts at the diaphragm than did the bellows-rebinned and bellows-triggered 4DMRI scans. Coronal scans were faster than sagittal scans because of the fewer slices and higher achievable acceleration factors. Navigator-triggered 4DMRI contains substantially fewer binning motion artifacts than bellows-rebinned and bellows-triggered 4DMRI, primarily owing to the deviation of the external from the internal surrogate. The present study compared 2 concurrent surrogates during the same 4DMRI scan and their resulting 4DMRI quality. The navigator-triggered 4DMRI scanning protocol should be preferred to the bellows-based, especially for coronal scans, for clinical respiratory motion simulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Magnetic resonance spectroscopic imaging at superresolution: Overview and perspectives.

PubMed

Kasten, Jeffrey; Klauser, Antoine; Lazeyras, François; Van De Ville, Dimitri

2016-02-01

The notion of non-invasive, high-resolution spatial mapping of metabolite concentrations has long enticed the medical community. While magnetic resonance spectroscopic imaging (MRSI) is capable of achieving the requisite spatio-spectral localization, it has traditionally been encumbered by significant resolution constraints that have thus far undermined its clinical utility. To surpass these obstacles, research efforts have primarily focused on hardware enhancements or the development of accelerated acquisition strategies to improve the experimental sensitivity per unit time. Concomitantly, a number of innovative reconstruction techniques have emerged as alternatives to the standard inverse discrete Fourier transform (DFT). While perhaps lesser known, these latter methods strive to effect commensurate resolution gains by exploiting known properties of the underlying MRSI signal in concert with advanced image and signal processing techniques. This review article aims to aggregate and provide an overview of the past few decades of so-called "superresolution" MRSI reconstruction methodologies, and to introduce readers to current state-of-the-art approaches. A number of perspectives are then offered as to the future of high-resolution MRSI, with a particular focus on translation into clinical settings. Copyright © 2015 Elsevier Inc. All rights reserved.

Image encryption using random sequence generated from generalized information domain

NASA Astrophysics Data System (ADS)

Xia-Yan, Zhang; Guo-Ji, Zhang; Xuan, Li; Ya-Zhou, Ren; Jie-Hua, Wu

2016-05-01

A novel image encryption method based on the random sequence generated from the generalized information domain and permutation-diffusion architecture is proposed. The random sequence is generated by reconstruction from the generalized information file and discrete trajectory extraction from the data stream. The trajectory address sequence is used to generate a P-box to shuffle the plain image while random sequences are treated as keystreams. A new factor called drift factor is employed to accelerate and enhance the performance of the random sequence generator. An initial value is introduced to make the encryption method an approximately one-time pad. Experimental results show that the random sequences pass the NIST statistical test with a high ratio and extensive analysis demonstrates that the new encryption scheme has superior security.

WE-G-18C-07: Accelerated Water/fat Separation in MRI for Radiotherapy Planning Using Multi-Band Imaging Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crijns, S; Stemkens, B; Sbrizzi, A

Purpose: Dixon sequences are used to characterize disease processes, obtain good fat or water separation in cases where fat suppression fails and to obtain pseudo-CT datasets. Dixon's method uses at least two images acquired with different echo times and thus requires prolonged acquisition times. To overcome associated problems (e.g., for DCE/cine-MRI), we propose to use a method for water/fat separation based on spectrally selective RF pulses. Methods: Two alternating RF pulses were used, that imposes a fat selective phase cycling over the phase encoding lines, which results in a spatial shift for fat in the reconstructed image, identical to thatmore » in CAIPIRINHA. Associated aliasing artefacts were resolved using the encoding power of a multi-element receiver array, analogous to SENSE. In vivo measurements were performed on a 1.5T clinical MR-scanner in a healthy volunteer's legs, using a four channel receiver coil. Gradient echo images were acquired with TE/TR = 2.3/4.7ms, flip angle 20°, FOV 45×22.5cm{sup 2}, matrix 480×216, slice thickness 5mm. Dixon images were acquired with TE,1/TE,2/TR=2.2/4.6/7ms. All image reconstructions were done in Matlab using the ReconFrame toolbox (Gyrotools, Zurich, CH). Results: RF pulse alternation yields a fat image offset from the water image. Hence the water and fat images fold over, which is resolved using in-plane SENSE reconstruction. Using the proposed technique, we achieved excellent water/fat separation comparable to Dixon images, while acquiring images at only one echo time. Conclusion: The proposed technique yields both inphase water and fat images at arbitrary echo times and requires only one measurement, thereby shortening the acquisition time by a factor 2. In future work the technique may be extended to a multi-band water/fat separation sequence that is able to achieve single point water/fat separation in multiple slices at once and hence yields higher speed-up factors.« less

Video-rate nanoscopy enabled by sCMOS camera-specific single-molecule localization algorithms

PubMed Central

Huang, Fang; Hartwich, Tobias M. P.; Rivera-Molina, Felix E.; Lin, Yu; Duim, Whitney C.; Long, Jane J.; Uchil, Pradeep D.; Myers, Jordan R.; Baird, Michelle A.; Mothes, Walther; Davidson, Michael W.; Toomre, Derek; Bewersdorf, Joerg

2013-01-01

Newly developed scientific complementary metal–oxide–semiconductor (sCMOS) cameras have the potential to dramatically accelerate data acquisition in single-molecule switching nanoscopy (SMSN) while simultaneously increasing the effective quantum efficiency. However, sCMOS-intrinsic pixel-dependent readout noise substantially reduces the localization precision and introduces localization artifacts. Here we present algorithms that overcome these limitations and provide unbiased, precise localization of single molecules at the theoretical limit. In combination with a multi-emitter fitting algorithm, we demonstrate single-molecule localization super-resolution imaging at up to 32 reconstructed images/second (recorded at 1,600–3,200 camera frames/second) in both fixed and living cells. PMID:23708387

[Development of a software for 3D virtual phantom design].

PubMed

Zou, Lian; Xie, Zhao; Wu, Qi

2014-02-01

In this paper, we present a 3D virtual phantom design software, which was developed based on object-oriented programming methodology and dedicated to medical physics research. This software was named Magical Phan tom (MPhantom), which is composed of 3D visual builder module and virtual CT scanner. The users can conveniently construct any complex 3D phantom, and then export the phantom as DICOM 3.0 CT images. MPhantom is a user-friendly and powerful software for 3D phantom configuration, and has passed the real scene's application test. MPhantom will accelerate the Monte Carlo simulation for dose calculation in radiation therapy and X ray imaging reconstruction algorithm research.

Joint 6D k-q Space Compressed Sensing for Accelerated High Angular Resolution Diffusion MRI.

PubMed

Cheng, Jian; Shen, Dinggang; Basser, Peter J; Yap, Pew-Thian

2015-01-01

High Angular Resolution Diffusion Imaging (HARDI) avoids the Gaussian. diffusion assumption that is inherent in Diffusion Tensor Imaging (DTI), and is capable of characterizing complex white matter micro-structure with greater precision. However, HARDI methods such as Diffusion Spectrum Imaging (DSI) typically require significantly more signal measurements than DTI, resulting in prohibitively long scanning times. One of the goals in HARDI research is therefore to improve estimation of quantities such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF) with a limited number of diffusion-weighted measurements. A popular approach to this problem, Compressed Sensing (CS), affords highly accurate signal reconstruction using significantly fewer (sub-Nyquist) data points than required traditionally. Existing approaches to CS diffusion MRI (CS-dMRI) mainly focus on applying CS in the q-space of diffusion signal measurements and fail to take into consideration information redundancy in the k-space. In this paper, we propose a framework, called 6-Dimensional Compressed Sensing diffusion MRI (6D-CS-dMRI), for reconstruction of the diffusion signal and the EAP from data sub-sampled in both 3D k-space and 3D q-space. To our knowledge, 6D-CS-dMRI is the first work that applies compressed sensing in the full 6D k-q space and reconstructs the diffusion signal in the full continuous q-space and the EAP in continuous displacement space. Experimental results on synthetic and real data demonstrate that, compared with full DSI sampling in k-q space, 6D-CS-dMRI yields excellent diffusion signal and EAP reconstruction with low root-mean-square error (RMSE) using 11 times less samples (3-fold reduction in k-space and 3.7-fold reduction in q-space).

Compression and accelerated rendering of volume data using DWT

NASA Astrophysics Data System (ADS)

Kamath, Preyas; Akleman, Ergun; Chan, Andrew K.

1998-09-01

2D images cannot convey information on object depth and location relative to the surfaces. The medical community is increasingly using 3D visualization techniques to view data from CT scans, MRI etc. 3D images provide more information on depth and location in the spatial domain to help surgeons making better diagnoses of the problem. 3D images can be constructed from 2D images using 3D scalar algorithms. With recent advances in communication techniques, it is possible for doctors to diagnose and plan treatment of a patient who lives at a remote location. It is made possible by transmitting relevant data of the patient via telephone lines. If this information is to be reconstructed in 3D, then 2D images must be transmitted. However 2D dataset storage occupies a lot of memory. In addition, visualization algorithms are slow. We describe in this paper a scheme which reduces the data transfer time by only transmitting information that the doctor wants. Compression is achieved by reducing the amount of data transfer. This is possible by using the 3D wavelet transform applied to 3D datasets. Since the wavelet transform is localized in frequency and spatial domain, we transmit detail only in the region where the doctor needs it. Since only ROM (Region of Interest) is reconstructed in detail, we need to render only ROI in detail, thus we can reduce the rendering time.

Image denoising for real-time MRI.

PubMed

Klosowski, Jakob; Frahm, Jens

2017-03-01

To develop an image noise filter suitable for MRI in real time (acquisition and display), which preserves small isolated details and efficiently removes background noise without introducing blur, smearing, or patch artifacts. The proposed method extends the nonlocal means algorithm to adapt the influence of the original pixel value according to a simple measure for patch regularity. Detail preservation is improved by a compactly supported weighting kernel that closely approximates the commonly used exponential weight, while an oracle step ensures efficient background noise removal. Denoising experiments were conducted on real-time images of healthy subjects reconstructed by regularized nonlinear inversion from radial acquisitions with pronounced undersampling. The filter leads to a signal-to-noise ratio (SNR) improvement of at least 60% without noticeable artifacts or loss of detail. The method visually compares to more complex state-of-the-art filters as the block-matching three-dimensional filter and in certain cases better matches the underlying noise model. Acceleration of the computation to more than 100 complex frames per second using graphics processing units is straightforward. The sensitivity of nonlocal means to small details can be significantly increased by the simple strategies presented here, which allows partial restoration of SNR in iteratively reconstructed images without introducing a noticeable time delay or image artifacts. Magn Reson Med 77:1340-1352, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Technical Note: Interleaved Bipolar Acquisition and Low-rank Reconstruction for Water-Fat Separation in MRI.

PubMed

Cho, JaeJin; Park, HyunWook

2018-05-17

To acquire interleaved bipolar data and reconstruct the full data using low-rank property for water fat separation. Bipolar acquisition suffers from issues related to gradient switching, the opposite gradient polarities, and other system imperfections, which prevent accurate water-fat separation. In this study, an interleaved bipolar acquisition scheme and a low-rank reconstruction method were proposed to reduce issues from the bipolar gradients while achieving a short imaging time. The proposed interleaved bipolar acquisition scheme collects echo-time signals from both gradient polarities; however, the sequence increases the imaging time. To reduce the imaging time, the signals were subsampled at every dimension of k-space. The low-rank property of the bipolar acquisition was defined and exploited to estimate the full data from the acquired subsampled data. To eliminate the bipolar issues, in the proposed method, the water-fat separation was performed separately for each gradient polarity, and the results for the positive and negative gradient polarities were combined after the water-fat separation. A phantom study and in-vivo experiments were conducted on a 3T Siemens Verio system. The results for the proposed method were compared with the results of the fully sampled interleaved bipolar acquisition and Soliman's method, which was the previous water-fat separation approach for reducing the issues of bipolar gradients and accelerating the interleaved bipolar acquisition. The proposed method provided accurate water and fat images without the issues of bipolar gradients and demonstrated a better performance compared with the results of the previous methods. The water-fat separation using the bipolar acquisition has several benefits including a short echo-spacing time. However, it suffers from bipolar-gradient issues such as strong gradient switching, system imperfection, and eddy current effects. This study demonstrated that accurate water-fat separated images can be obtained using the proposed interleaved bipolar acquisition and low-rank reconstruction by using the benefits of the bipolar acquisition while reducing the bipolar-gradient issues with a short imaging time. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A computational approach to real-time image processing for serial time-encoded amplified microscopy

NASA Astrophysics Data System (ADS)

Oikawa, Minoru; Hiyama, Daisuke; Hirayama, Ryuji; Hasegawa, Satoki; Endo, Yutaka; Sugie, Takahisa; Tsumura, Norimichi; Kuroshima, Mai; Maki, Masanori; Okada, Genki; Lei, Cheng; Ozeki, Yasuyuki; Goda, Keisuke; Shimobaba, Tomoyoshi

2016-03-01

High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.

Serial Section Scanning Electron Microscopy (S3EM) on Silicon Wafers for Ultra-Structural Volume Imaging of Cells and Tissues

PubMed Central

Horstmann, Heinz; Körber, Christoph; Sätzler, Kurt; Aydin, Daniel; Kuner, Thomas

2012-01-01

High resolution, three-dimensional (3D) representations of cellular ultrastructure are essential for structure function studies in all areas of cell biology. While limited subcellular volumes have been routinely examined using serial section transmission electron microscopy (ssTEM), complete ultrastructural reconstructions of large volumes, entire cells or even tissue are difficult to achieve using ssTEM. Here, we introduce a novel approach combining serial sectioning of tissue with scanning electron microscopy (SEM) using a conductive silicon wafer as a support. Ribbons containing hundreds of 35 nm thick sections can be generated and imaged on the wafer at a lateral pixel resolution of 3.7 nm by recording the backscattered electrons with the in-lens detector of the SEM. The resulting electron micrographs are qualitatively comparable to those obtained by conventional TEM. S3EM images of the same region of interest in consecutive sections can be used for 3D reconstructions of large structures. We demonstrate the potential of this approach by reconstructing a 31.7 µm3 volume of a calyx of Held presynaptic terminal. The approach introduced here, Serial Section SEM (S3EM), for the first time provides the possibility to obtain 3D ultrastructure of large volumes with high resolution and to selectively and repetitively home in on structures of interest. S3EM accelerates process duration, is amenable to full automation and can be implemented with standard instrumentation. PMID:22523574

Serial section scanning electron microscopy (S3EM) on silicon wafers for ultra-structural volume imaging of cells and tissues.

PubMed

Horstmann, Heinz; Körber, Christoph; Sätzler, Kurt; Aydin, Daniel; Kuner, Thomas

2012-01-01

High resolution, three-dimensional (3D) representations of cellular ultrastructure are essential for structure function studies in all areas of cell biology. While limited subcellular volumes have been routinely examined using serial section transmission electron microscopy (ssTEM), complete ultrastructural reconstructions of large volumes, entire cells or even tissue are difficult to achieve using ssTEM. Here, we introduce a novel approach combining serial sectioning of tissue with scanning electron microscopy (SEM) using a conductive silicon wafer as a support. Ribbons containing hundreds of 35 nm thick sections can be generated and imaged on the wafer at a lateral pixel resolution of 3.7 nm by recording the backscattered electrons with the in-lens detector of the SEM. The resulting electron micrographs are qualitatively comparable to those obtained by conventional TEM. S(3)EM images of the same region of interest in consecutive sections can be used for 3D reconstructions of large structures. We demonstrate the potential of this approach by reconstructing a 31.7 µm(3) volume of a calyx of Held presynaptic terminal. The approach introduced here, Serial Section SEM (S(3)EM), for the first time provides the possibility to obtain 3D ultrastructure of large volumes with high resolution and to selectively and repetitively home in on structures of interest. S(3)EM accelerates process duration, is amenable to full automation and can be implemented with standard instrumentation.

Dictionary learning and time sparsity in dynamic MRI.

PubMed

Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

2012-01-01

Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

NASA Astrophysics Data System (ADS)

Li, Zhengyan; Zgadzaj, Rafal; Wang, Xiaoming; Reed, Stephen; Dong, Peng; Downer, Michael C.

2010-11-01

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index "bubble" in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the "bubble". Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the "bubble" from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporal Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.

A 2D MTF approach to evaluate and guide dynamic imaging developments.

PubMed

Chao, Tzu-Cheng; Chung, Hsiao-Wen; Hoge, W Scott; Madore, Bruno

2010-02-01

As the number and complexity of partially sampled dynamic imaging methods continue to increase, reliable strategies to evaluate performance may prove most useful. In the present work, an analytical framework to evaluate given reconstruction methods is presented. A perturbation algorithm allows the proposed evaluation scheme to perform robustly without requiring knowledge about the inner workings of the method being evaluated. A main output of the evaluation process consists of a two-dimensional modulation transfer function, an easy-to-interpret visual rendering of a method's ability to capture all combinations of spatial and temporal frequencies. Approaches to evaluate noise properties and artifact content at all spatial and temporal frequencies are also proposed. One fully sampled phantom and three fully sampled cardiac cine datasets were subsampled (R = 4 and 8) and reconstructed with the different methods tested here. A hybrid method, which combines the main advantageous features observed in our assessments, was proposed and tested in a cardiac cine application, with acceleration factors of 3.5 and 6.3 (skip factors of 4 and 8, respectively). This approach combines features from methods such as k-t sensitivity encoding, unaliasing by Fourier encoding the overlaps in the temporal dimension-sensitivity encoding, generalized autocalibrating partially parallel acquisition, sensitivity profiles from an array of coils for encoding and reconstruction in parallel, self, hybrid referencing with unaliasing by Fourier encoding the overlaps in the temporal dimension and generalized autocalibrating partially parallel acquisition, and generalized autocalibrating partially parallel acquisition-enhanced sensitivity maps for sensitivity encoding reconstructions.

CT image reconstruction with half precision floating-point values.

PubMed

Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc

2011-07-01

Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow's reconstruction hardware (CPU and GPU) that allows implementing the forward projection and backprojection steps, which are the computationally most demanding parts of any reconstruction algorithm, much more efficiently. Instead of the standard 32 bit floating-point values (float), a recently standardized floating-point value with 16 bit (half) is adopted for data representation in image domain and in rawdata domain. The reduction in the total data amount reduces the traffic on the memory bus, which is the bottleneck of today's high-performance algorithms, by 50%. In CT simulations and CT measurements, float reconstructions (gold standard) and half reconstructions are visually compared via difference images and by quantitative image quality evaluation. This is done for analytical reconstruction (filtered backprojection) and iterative reconstruction (ordered subset SART). The magnitude of quantization noise, which is caused by a reduction in the data precision of both rawdata and image data during image reconstruction, is negligible. This is clearly shown for filtered backprojection and iterative ordered subset SART reconstruction. In filtered backprojection, the implementation of the backprojection should be optimized for low data precision if the image data are represented in half format. In ordered subset SART image reconstruction, no adaptations are necessary and the convergence speed remains unchanged. Half precision floating-point values allow to speed up CT image reconstruction without compromising image quality.

Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE).

PubMed

Zhu, Chengcheng; Tian, Bing; Chen, Luguang; Eisenmenger, Laura; Raithel, Esther; Forman, Christoph; Ahn, Sinyeob; Laub, Gerhard; Liu, Qi; Lu, Jianping; Liu, Jing; Hess, Christopher; Saloner, David

2018-06-01

Develop and optimize an accelerated, high-resolution (0.5 mm isotropic) 3D black blood MRI technique to reduce scan time for whole-brain intracranial vessel wall imaging. A 3D accelerated T 1 -weighted fast-spin-echo prototype sequence using compressed sensing (CS-SPACE) was developed at 3T. Both the acquisition [echo train length (ETL), under-sampling factor] and reconstruction parameters (regularization parameter, number of iterations) were first optimized in 5 healthy volunteers. Ten patients with a variety of intracranial vascular disease presentations (aneurysm, atherosclerosis, dissection, vasculitis) were imaged with SPACE and optimized CS-SPACE, pre and post Gd contrast. Lumen/wall area, wall-to-lumen contrast ratio (CR), enhancement ratio (ER), sharpness, and qualitative scores (1-4) by two radiologists were recorded. The optimized CS-SPACE protocol has ETL 60, 20% k-space under-sampling, 0.002 regularization factor with 20 iterations. In patient studies, CS-SPACE and conventional SPACE had comparable image scores both pre- (3.35 ± 0.85 vs. 3.54 ± 0.65, p = 0.13) and post-contrast (3.72 ± 0.58 vs. 3.53 ± 0.57, p = 0.15), but the CS-SPACE acquisition was 37% faster (6:48 vs. 10:50). CS-SPACE agreed with SPACE for lumen/wall area, ER measurements and sharpness, but marginally reduced the CR. In the evaluation of intracranial vascular disease, CS-SPACE provides a substantial reduction in scan time compared to conventional T 1 -weighted SPACE while maintaining good image quality.

Gctf: Real-time CTF determination and correction

PubMed Central

Zhang, Kai

2016-01-01

Accurate estimation of the contrast transfer function (CTF) is critical for a near-atomic resolution cryo electron microscopy (cryoEM) reconstruction. Here, a GPU-accelerated computer program, Gctf, for accurate and robust, real-time CTF determination is presented. The main target of Gctf is to maximize the cross-correlation of a simulated CTF with the logarithmic amplitude spectra (LAS) of observed micrographs after background subtraction. Novel approaches in Gctf improve both speed and accuracy. In addition to GPU acceleration (e.g. 10–50×), a fast ‘1-dimensional search plus 2-dimensional refinement (1S2R)’ procedure further speeds up Gctf. Based on the global CTF determination, the local defocus for each particle and for single frames of movies is accurately refined, which improves CTF parameters of all particles for subsequent image processing. Novel diagnosis method using equiphase averaging (EPA) and self-consistency verification procedures have also been implemented in the program for practical use, especially for aims of near-atomic reconstruction. Gctf is an independent program and the outputs can be easily imported into other cryoEM software such as Relion (Scheres, 2012) and Frealign (Grigorieff, 2007). The results from several representative datasets are shown and discussed in this paper. PMID:26592709

Combined algorithmic and GPU acceleration for ultra-fast circular conebeam backprojection

NASA Astrophysics Data System (ADS)

Brokish, Jeffrey; Sack, Paul; Bresler, Yoram

2010-04-01

In this paper, we describe the first implementation and performance of a fast O(N3logN) hierarchical backprojection algorithm for cone beam CT with a circular trajectory1,developed on a modern Graphics Processing Unit (GPU). The resulting tomographic backprojection system for 3D cone beam geometry combines speedup through algorithmic improvements provided by the hierarchical backprojection algorithm with speedup from a massively parallel hardware accelerator. For data parameters typical in diagnostic CT and using a mid-range GPU card, we report reconstruction speeds of up to 360 frames per second, and relative speedup of almost 6x compared to conventional backprojection on the same hardware. The significance of these results is twofold. First, they demonstrate that the reduction in operation counts demonstrated previously for the FHBP algorithm can be translated to a comparable run-time improvement in a massively parallel hardware implementation, while preserving stringent diagnostic image quality. Second, the dramatic speedup and throughput numbers achieved indicate the feasibility of systems based on this technology, which achieve real-time 3D reconstruction for state-of-the art diagnostic CT scanners with small footprint, high-reliability, and affordable cost.

Prospective study of cone-beam computed tomography image-guided radiotherapy for prone accelerated partial breast irradiation.

PubMed

Jozsef, Gabor; DeWyngaert, J Keith; Becker, Stewart J; Lymberis, Stella; Formenti, Silvia C

2011-10-01

To report setup variations during prone accelerated partial breast irradiation (APBI). New York University (NYU) 07-582 is an institutional review board-approved protocol of cone-beam computed tomography (CBCT) to deliver image-guided ABPI in the prone position. Eligible are postmenopausal women with pT1 breast cancer excised with negative margins and no nodal involvement. A total dose of 30 Gy in five daily fractions of 6 Gy are delivered to the planning target volume (the tumor cavity with 1.5-cm margin) by image-guided radiotherapy. Patients are set up prone, on a dedicated mattress, used for both simulation and treatment. After positioning with skin marks and lasers, CBCTs are performed and the images are registered to the planning CT. The resulting shifts (setup corrections) are recorded in the three principal directions and applied. Portal images are taken for verification. If they differ from the planning digital reconstructed radiographs, the patient is reset, and a new CBCT is taken. 70 consecutive patients have undergone a total of 343 CBCTs: 7 patients had four of five planned CBCTs performed. Seven CBCTs (2%) required to be repeated because of misalignment in the comparison between portal and digital reconstructed radiograph image after the first CBCT. The mean shifts and standard deviations in the anterior-posterior (AP), superior-inferior (SI), and medial-lateral (ML) directions were -0.19 (0.54), -0.02 (0.33), and -0.02 (0.43) cm, respectively. The average root mean squares of the daily shifts were 0.50 (0.28), 0.29 (0.17), and 0.38 (0.20). A conservative margin formula resulted in a recommended margin of 1.26, 0.73, 0.96 cm in the AP, SI, and ML directions. CBCTs confirmed that the NYU prone APBI setup and treatment technique are reproducible, with interfraction variation comparable to those reported for supine setup. The currently applied margin (1.5 cm) adequately compensates for the setup variation detected. Copyright © 2011 Elsevier Inc. All rights reserved.

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eck, Brendan L.; Fahmi, Rachid; Miao, Jun

2015-10-15

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated usingmore » a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.« less

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera

NASA Astrophysics Data System (ADS)

Cruz Perez, Carlos; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera.

PubMed

Perez, Carlos Cruz; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront.

PubMed

Gao, Jingkun; Deng, Bin; Qin, Yuliang; Wang, Hongqiang; Li, Xiang

2016-12-14

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

Fast viscosity solutions for shape from shading under a more realistic imaging model

NASA Astrophysics Data System (ADS)

Wang, Guohui; Han, Jiuqiang; Jia, Honghai; Zhang, Xinman

2009-11-01

Shape from shading (SFS) has been a classical and important problem in the domain of computer vision. The goal of SFS is to reconstruct the 3-D shape of an object from its 2-D intensity image. To this end, an image irradiance equation describing the relation between the shape of a surface and its corresponding brightness variations is used. Then it is derived as an explicit partial differential equation (PDE). Using the nonlinear programming principle, we propose a detailed solution to Prados and Faugeras's implicit scheme for approximating the viscosity solution of the resulting PDE. Furthermore, by combining implicit and semi-implicit schemes, a new approximation scheme is presented. In order to accelerate the convergence speed, we adopt the Gauss-Seidel idea and alternating sweeping strategy to the approximation schemes. Experimental results on both synthetic and real images are performed to demonstrate that the proposed methods are fast and accurate.

Advances in Heavy Ion Beam Probe Technology and Operation on MST

NASA Astrophysics Data System (ADS)

Demers, D. R.; Connor, K. A.; Schoch, P. M.; Radke, R. J.; Anderson, J. K.; Craig, D.; den Hartog, D. J.

2003-10-01

A technique to map the magnetic field of a plasma via spectral imaging is being developed with the Heavy Ion Beam Probe on the Madison Symmetric Torus. The technique will utilize two-dimensional images of the ion beam in the plasma, acquired by two CCD cameras, to generate a three-dimensional reconstruction of the beam trajectory. This trajectory, and the known beam ion mass, energy and charge-state, will be used to determine the magnetic field of the plasma. A suitable emission line has not yet been observed since radiation from the MST plasma is both broadband and intense. An effort to raise the emission intensity from the ion beam by increasing beam focus and current has been undertaken. Simulations of the accelerator ion optics and beam characteristics led to a technique, confirmed by experiment, that achieves a narrower beam and marked increase in ion current near the plasma surface. The improvements arising from these simulations will be discussed. Realization of the magnetic field mapping technique is contingent upon accurate reconstruction of the beam trajectory from the camera images. Simulations of two camera CCD images, including the interior of MST, its various landmarks and beam trajectories have been developed. These simulations accept user input such as camera locations, resolution via pixellization and noise. The quality of the images simulated with these and other variables will help guide the selection of viewing port pairs, image size and camera specifications. The results of these simulations will be presented.

SU-F-T-489: 4-Years Experience of QA in TomoTherapy MVCT: What Do We Look Out For?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, F; Chan, K

2016-06-15

Purpose: To evaluate the QA results of TomoTherapy MVCT from March 2012 to February 2016, and to identify issues that may affect consistency in HU numbers and reconstructed treatment dose in MVCT. Methods: Monthly QA was performed on our TomoHD system. Phantom with rod inserts of various mass densities was imaged in MVCT and compared to baseline to evaluate HU number consistency. To evaluate treatment dose reconstructed by delivered sinogram and MVCT, a treatment plan was designed on a humanoid skull phantom. The phantom was imaged with MVCT and treatment plan was delivered to obtain the sinogram. The dose reconstructedmore » with the Planned Adaptive software was compared to the dose in the original plan. The QA tolerance for HU numbers was ±30 HU, and ±2% for discrepancy between original plan dose and reconstructed dose. Tolerances were referenced to AAPM TG148. Results: Several technical modifications or maintenance activities to the system have been identified which affected QA Results: 1) Upgrade in console system software which added a weekly HU calibration procedure; 2) Linac or MLC replacement leading to change in Accelerator Output Machine (AOM) parameters; 3) Upgrade in planning system algorithm affecting MVCT dose reconstruction. These events caused abrupt changes in QA results especially for the reconstructed dose. In the past 9 months, when no such modifications were done to the system, reconstructed dose was consistent with maximum deviation from baseline less than 0.6%. The HU number deviated less than 5HU. Conclusion: Routine QA is essential for MVCT, especially if the MVCT is used for daily dose reconstruction to monitor delivered dose to patients. Several technical events which may affect consistency of this are software changes, linac or MLC replacement. QA results reflected changes which justify re-calibration or system adjustment. In normal circumstances, the system should be relatively stable and quarterly QA may be sufficient.« less

GPU accelerated generation of digitally reconstructed radiographs for 2-D/3-D image registration.

PubMed

Dorgham, Osama M; Laycock, Stephen D; Fisher, Mark H

2012-09-01

Recent advances in programming languages for graphics processing units (GPUs) provide developers with a convenient way of implementing applications which can be executed on the CPU and GPU interchangeably. GPUs are becoming relatively cheap, powerful, and widely available hardware components, which can be used to perform intensive calculations. The last decade of hardware performance developments shows that GPU-based computation is progressing significantly faster than CPU-based computation, particularly if one considers the execution of highly parallelisable algorithms. Future predictions illustrate that this trend is likely to continue. In this paper, we introduce a way of accelerating 2-D/3-D image registration by developing a hybrid system which executes on the CPU and utilizes the GPU for parallelizing the generation of digitally reconstructed radiographs (DRRs). Based on the advancements of the GPU over the CPU, it is timely to exploit the benefits of many-core GPU technology by developing algorithms for DRR generation. Although some previous work has investigated the rendering of DRRs using the GPU, this paper investigates approximations which reduce the computational overhead while still maintaining a quality consistent with that needed for 2-D/3-D registration with sufficient accuracy to be clinically acceptable in certain applications of radiation oncology. Furthermore, by comparing implementations of 2-D/3-D registration on the CPU and GPU, we investigate current performance and propose an optimal framework for PC implementations addressing the rigid registration problem. Using this framework, we are able to render DRR images from a 256×256×133 CT volume in ~24 ms using an NVidia GeForce 8800 GTX and in ~2 ms using NVidia GeForce GTX 580. In addition to applications requiring fast automatic patient setup, these levels of performance suggest image-guided radiation therapy at video frame rates is technically feasible using relatively low cost PC architecture.

Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

PubMed

Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

2014-12-01

To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality. © RSNA, 2014.

Multi-GPU Acceleration of Branchless Distance Driven Projection and Backprojection for Clinical Helical CT.

PubMed

Mitra, Ayan; Politte, David G; Whiting, Bruce R; Williamson, Jeffrey F; O'Sullivan, Joseph A

2017-01-01

Model-based image reconstruction (MBIR) techniques have the potential to generate high quality images from noisy measurements and a small number of projections which can reduce the x-ray dose in patients. These MBIR techniques rely on projection and backprojection to refine an image estimate. One of the widely used projectors for these modern MBIR based technique is called branchless distance driven (DD) projection and backprojection. While this method produces superior quality images, the computational cost of iterative updates keeps it from being ubiquitous in clinical applications. In this paper, we provide several new parallelization ideas for concurrent execution of the DD projectors in multi-GPU systems using CUDA programming tools. We have introduced some novel schemes for dividing the projection data and image voxels over multiple GPUs to avoid runtime overhead and inter-device synchronization issues. We have also reduced the complexity of overlap calculation of the algorithm by eliminating the common projection plane and directly projecting the detector boundaries onto image voxel boundaries. To reduce the time required for calculating the overlap between the detector edges and image voxel boundaries, we have proposed a pre-accumulation technique to accumulate image intensities in perpendicular 2D image slabs (from a 3D image) before projection and after backprojection to ensure our DD kernels run faster in parallel GPU threads. For the implementation of our iterative MBIR technique we use a parallel multi-GPU version of the alternating minimization (AM) algorithm with penalized likelihood update. The time performance using our proposed reconstruction method with Siemens Sensation 16 patient scan data shows an average of 24 times speedup using a single TITAN X GPU and 74 times speedup using 3 TITAN X GPUs in parallel for combined projection and backprojection.

Reconstruction of transient vibration and sound radiation of an impacted plate using time domain plane wave superposition method

NASA Astrophysics Data System (ADS)

Geng, Lin; Zhang, Xiao-Zheng; Bi, Chuan-Xing

2015-05-01

Time domain plane wave superposition method is extended to reconstruct the transient pressure field radiated by an impacted plate and the normal acceleration of the plate. In the extended method, the pressure measured on the hologram plane is expressed as a superposition of time convolutions between the time-wavenumber normal acceleration spectrum on a virtual source plane and the time domain propagation kernel relating the pressure on the hologram plane to the normal acceleration spectrum on the virtual source plane. By performing an inverse operation, the normal acceleration spectrum on the virtual source plane can be obtained by an iterative solving process, and then taken as the input to reconstruct the whole pressure field and the normal acceleration of the plate. An experiment of a clamped rectangular steel plate impacted by a steel ball is presented. The experimental results demonstrate that the extended method is effective in visualizing the transient vibration and sound radiation of an impacted plate in both time and space domains, thus providing the important information for overall understanding the vibration and sound radiation of the plate.

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Use of pattern recognition for unaliasing simultaneously acquired slices in simultaneous multislice MR fingerprinting.

PubMed

Jiang, Yun; Ma, Dan; Bhat, Himanshu; Ye, Huihui; Cauley, Stephen F; Wald, Lawrence L; Setsompop, Kawin; Griswold, Mark A

2017-11-01

The purpose of this study is to accelerate an MR fingerprinting (MRF) acquisition by using a simultaneous multislice method. A multiband radiofrequency (RF) pulse was designed to excite two slices with different flip angles and phases. The signals of two slices were driven to be as orthogonal as possible. The mixed and undersampled MRF signal was matched to two dictionaries to retrieve T 1 and T 2 maps of each slice. Quantitative results from the proposed method were validated with the gold-standard spin echo methods in a phantom. T 1 and T 2 maps of in vivo human brain from two simultaneously acquired slices were also compared to the results of fast imaging with steady-state precession based MRF method (MRF-FISP) with a single-band RF excitation. The phantom results showed that the simultaneous multislice imaging MRF-FISP method quantified the relaxation properties accurately compared to the gold-standard spin echo methods. T 1 and T 2 values of in vivo brain from the proposed method also matched the results from the normal MRF-FISP acquisition. T 1 and T 2 values can be quantified at a multiband acceleration factor of two using our proposed acquisition even in a single-channel receive coil. Further acceleration could be achieved by combining this method with parallel imaging or iterative reconstruction. Magn Reson Med 78:1870-1876, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

General phase regularized reconstruction using phase cycling.

PubMed

Ong, Frank; Cheng, Joseph Y; Lustig, Michael

2018-07-01

To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase regularized reconstruction algorithm was proposed to enable various joint reconstruction of partial Fourier imaging, water-fat imaging and flow imaging, along with parallel imaging (PI) and compressed sensing (CS). Since phase regularized reconstruction is inherently non-convex and sensitive to phase wraps in the initial solution, a reconstruction technique, named phase cycling, was proposed to render the overall algorithm invariant to phase wraps. The proposed method was applied to retrospectively under-sampled in vivo datasets and compared with state of the art reconstruction methods. Phase cycling reconstructions showed reduction of artifacts compared to reconstructions without phase cycling and achieved similar performances as state of the art results in partial Fourier, water-fat and divergence-free regularized flow reconstruction. Joint reconstruction of partial Fourier + water-fat imaging + PI + CS, and partial Fourier + divergence-free regularized flow imaging + PI + CS were demonstrated. The proposed phase cycling reconstruction provides an alternative way to perform phase regularized reconstruction, without the need to perform phase unwrapping. It is robust to the choice of initial solutions and encourages the joint reconstruction of phase imaging applications. Magn Reson Med 80:112-125, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Respiratory motion guided four dimensional cone beam computed tomography: encompassing irregular breathing

NASA Astrophysics Data System (ADS)

O'Brien, Ricky T.; Cooper, Benjamin J.; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J.

2014-02-01

Four dimensional cone beam computed tomography (4DCBCT) images suffer from angular under sampling and bunching of projections due to a lack of feedback between the respiratory signal and the acquisition system. To address this problem, respiratory motion guided 4DCBCT (RMG-4DCBCT) regulates the gantry velocity and projection time interval, in response to the patient’s respiratory signal, with the aim of acquiring evenly spaced projections in a number of phase or displacement bins during the respiratory cycle. Our previous study of RMG-4DCBCT was limited to sinusoidal breathing traces. Here we expand on that work to provide a practical algorithm for the case of real patient breathing data. We give a complete description of RMG-4DCBCT including full details on how to implement the algorithms to determine when to move the gantry and when to acquire projections in response to the patient’s respiratory signal. We simulate a realistic working RMG-4DCBCT system using 112 breathing traces from 24 lung cancer patients. Acquisition used phase-based binning and parameter settings typically used on commercial 4DCBCT systems (4 min acquisition time, 1200 projections across 10 respiratory bins), with the acceleration and velocity constraints of current generation linear accelerators. We quantified streaking artefacts and image noise for conventional and RMG-4DCBCT methods by reconstructing projection data selected from an oversampled set of Catphan phantom projections. RMG-4DCBCT allows us to optimally trade-off image quality, acquisition time and image dose. For example, for the same image quality and acquisition time as conventional 4DCBCT approximately half the imaging dose is needed. Alternatively, for the same imaging dose, the image quality as measured by the signal to noise ratio, is improved by 63% on average. C-arm cone beam computed tomography systems, with an acceleration up to 200°/s2, a velocity up to 100°/s and the acquisition of 80 projections per second, allow the image acquisition time to be reduced to below 60 s. We have made considerable progress towards realizing a system to reduce projection clustering in conventional 4DCBCT imaging and hence reduce the imaging dose to the patient.

Improved adaptive genetic algorithm with sparsity constraint applied to thermal neutron CT reconstruction of two-phase flow

NASA Astrophysics Data System (ADS)

Yan, Mingfei; Hu, Huasi; Otake, Yoshie; Taketani, Atsushi; Wakabayashi, Yasuo; Yanagimachi, Shinzo; Wang, Sheng; Pan, Ziheng; Hu, Guang

2018-05-01

Thermal neutron computer tomography (CT) is a useful tool for visualizing two-phase flow due to its high imaging contrast and strong penetrability of neutrons for tube walls constructed with metallic material. A novel approach for two-phase flow CT reconstruction based on an improved adaptive genetic algorithm with sparsity constraint (IAGA-SC) is proposed in this paper. In the algorithm, the neighborhood mutation operator is used to ensure the continuity of the reconstructed object. The adaptive crossover probability P c and mutation probability P m are improved to help the adaptive genetic algorithm (AGA) achieve the global optimum. The reconstructed results for projection data, obtained from Monte Carlo simulation, indicate that the comprehensive performance of the IAGA-SC algorithm exceeds the adaptive steepest descent-projection onto convex sets (ASD-POCS) algorithm in restoring typical and complex flow regimes. It especially shows great advantages in restoring the simply connected flow regimes and the shape of object. In addition, the CT experiment for two-phase flow phantoms was conducted on the accelerator-driven neutron source to verify the performance of the developed IAGA-SC algorithm.

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Pan, X; Stayman, J

2014-06-15

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less

A review of 3D first-pass, whole-heart, myocardial perfusion cardiovascular magnetic resonance.

PubMed

Fair, Merlin J; Gatehouse, Peter D; DiBella, Edward V R; Firmin, David N

2015-08-01

A comprehensive review is undertaken of the methods available for 3D whole-heart first-pass perfusion (FPP) and their application to date, with particular focus on possible acceleration techniques. Following a summary of the parameters typically desired of 3D FPP methods, the review explains the mechanisms of key acceleration techniques and their potential use in FPP for attaining 3D acquisitions. The mechanisms include rapid sequences, non-Cartesian k-space trajectories, reduced k-space acquisitions, parallel imaging reconstructions and compressed sensing. An attempt is made to explain, rather than simply state, the varying methods with the hope that it will give an appreciation of the different components making up a 3D FPP protocol. Basic estimates demonstrating the required total acceleration factors in typical 3D FPP cases are included, providing context for the extent that each acceleration method can contribute to the required imaging speed, as well as potential limitations in present 3D FPP literature. Although many 3D FPP methods are too early in development for the type of clinical trials required to show any clear benefit over current 2D FPP methods, the review includes the small but growing quantity of clinical research work already using 3D FPP, alongside the more technical work. Broader challenges concerning FPP such as quantitative analysis are not covered, but challenges with particular impact on 3D FPP methods, particularly with regards to motion effects, are discussed along with anticipated future work in the field.

GPU-accelerated depth map generation for X-ray simulations of complex CAD geometries

NASA Astrophysics Data System (ADS)

Grandin, Robert J.; Young, Gavin; Holland, Stephen D.; Krishnamurthy, Adarsh

2018-04-01

Interactive x-ray simulations of complex computer-aided design (CAD) models can provide valuable insights for better interpretation of the defect signatures such as porosity from x-ray CT images. Generating the depth map along a particular direction for the given CAD geometry is the most compute-intensive step in x-ray simulations. We have developed a GPU-accelerated method for real-time generation of depth maps of complex CAD geometries. We preprocess complex components designed using commercial CAD systems using a custom CAD module and convert them into a fine user-defined surface tessellation. Our CAD module can be used by different simulators as well as handle complex geometries, including those that arise from complex castings and composite structures. We then make use of a parallel algorithm that runs on a graphics processing unit (GPU) to convert the finely-tessellated CAD model to a voxelized representation. The voxelized representation can enable heterogeneous modeling of the volume enclosed by the CAD model by assigning heterogeneous material properties in specific regions. The depth maps are generated from this voxelized representation with the help of a GPU-accelerated ray-casting algorithm. The GPU-accelerated ray-casting method enables interactive (> 60 frames-per-second) generation of the depth maps of complex CAD geometries. This enables arbitrarily rotation and slicing of the CAD model, leading to better interpretation of the x-ray images by the user. In addition, the depth maps can be used to aid directly in CT reconstruction algorithms.

EIT image reconstruction with four dimensional regularization.

PubMed

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

COMPARISON OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION (ASIR™) AND MODEL-BASED ITERATIVE RECONSTRUCTION (VEO™) FOR PAEDIATRIC ABDOMINAL CT EXAMINATIONS: AN OBSERVER PERFORMANCE STUDY OF DIAGNOSTIC IMAGE QUALITY.

PubMed

Hultenmo, Maria; Caisander, Håkan; Mack, Karsten; Thilander-Klang, Anne

2016-06-01

The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR™) and model-based IR (Veo™)-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft™ convolution kernel and with the Veo algorithm. The thickness of the reconstructed images was 2.5 or 5 mm depending on the scanning protocol used. Four radiologists graded the delineation of six abdominal structures and the diagnostic usefulness of the image quality. The Veo reconstruction significantly improved the visibility of most of the structures compared with ASiR in all subgroups of images. For coronal images, the Veo reconstruction resulted in significantly improved ratings of the diagnostic use of the image quality compared with the ASiR reconstruction. This was not seen for the axial images. The greatest improvement using Veo reconstruction was observed for the 2.5 mm coronal slices. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

GPU-accelerated algorithms for compressed signals recovery with application to astronomical imagery deblurring

NASA Astrophysics Data System (ADS)

Fiandrotti, Attilio; Fosson, Sophie M.; Ravazzi, Chiara; Magli, Enrico

2018-04-01

Compressive sensing promises to enable bandwidth-efficient on-board compression of astronomical data by lifting the encoding complexity from the source to the receiver. The signal is recovered off-line, exploiting GPUs parallel computation capabilities to speedup the reconstruction process. However, inherent GPU hardware constraints limit the size of the recoverable signal and the speedup practically achievable. In this work, we design parallel algorithms that exploit the properties of circulant matrices for efficient GPU-accelerated sparse signals recovery. Our approach reduces the memory requirements, allowing us to recover very large signals with limited memory. In addition, it achieves a tenfold signal recovery speedup thanks to ad-hoc parallelization of matrix-vector multiplications and matrix inversions. Finally, we practically demonstrate our algorithms in a typical application of circulant matrices: deblurring a sparse astronomical image in the compressed domain.

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Zhengyan; Zgadzaj, Rafal; Wang Xiaoming

2010-11-04

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index 'bubble' in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the 'bubble'. Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the 'bubble' from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporalmore » Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.« less

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

PubMed Central

van Aart, Evert; Sepasian, Neda; Jalba, Andrei; Vilanova, Anna

2011-01-01

Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a Graphics Processing Unit (GPU). This algorithm, which is based on the calculation of geodesics, has shown promising results for both synthetic and real data, but is limited in its applicability by its high computational requirements. We present a solution which uses the parallelism offered by modern GPUs, in combination with the CUDA platform by NVIDIA, to significantly reduce the execution time of the fiber-tracking algorithm. Compared to a multithreaded CPU implementation of the same algorithm, our GPU mapping achieves a speedup factor of up to 40 times. PMID:21941525

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

PubMed

Nakarmi, Ukash; Wang, Yanhua; Lyu, Jingyuan; Liang, Dong; Ying, Leslie

2017-11-01

While many low rank and sparsity-based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub-Nyquist data. Within this framework, many existing algorithms can be extended to kernel framework with nonlinear models. In particular, we have developed a novel algorithm with a kernel-based low-rank model generalizing the conventional low rank formulation. The algorithm consists of manifold learning using kernel, low rank enforcement in feature space, and preimaging with data consistency. Extensive simulation and experiment results show that the proposed method surpasses the conventional low-rank-modeled approaches for dMRI.

Level-set-based reconstruction algorithm for EIT lung images: first clinical results.

PubMed

Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy

2012-05-01

We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.

Co-registered Frequency-Domain Photoacoustic Radar and Ultrasound System for Subsurface Imaging in Turbid Media

NASA Astrophysics Data System (ADS)

Dovlo, Edem; Lashkari, Bahman; Mandelis, Andreas

2016-03-01

Frequency-domain photoacoustic radar (FD-PAR) imaging of absorbers in turbid media and their comparison and/or validation as well as co-registration with their corresponding ultrasound (US) images are demonstrated in this paper. Also presented are the FD-PAR tomography and the effects of reducing the number of scan lines (or angles) on image quality, resolution, and contrast. The FD-PAR modality uses intensity-modulated (coded) continuous wave laser sources driven by frequency-swept (chirp) waveforms. The spatial cross-correlation function between the PA response and the reference signal used for laser source modulation produces the reconstructed image. Live animal testing is demonstrated, and images of comparable signal-to-noise ratio, contrast, and spatial resolution were obtained. Various image improvement techniques to further reduce absorber spread and artifacts in the images such as normalization, filtering, and amplification were also investigated. The co-registered image produced from the combined US and PA images provides more information than both images independently. The significance of this work lies in the fact that achieving PA imaging functionality on a commercial ultrasound instrument could accelerate its clinical acceptance and use. This work is aimed at functional PA imaging of small animals in vivo.

Image transmission system using adaptive joint source and channel decoding

NASA Astrophysics Data System (ADS)

Liu, Weiliang; Daut, David G.

2005-03-01

In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.

Multichannel Compressive Sensing MRI Using Noiselet Encoding

PubMed Central

Pawar, Kamlesh; Egan, Gary; Zhang, Jingxin

2015-01-01

The incoherence between measurement and sparsifying transform matrices and the restricted isometry property (RIP) of measurement matrix are two of the key factors in determining the performance of compressive sensing (CS). In CS-MRI, the randomly under-sampled Fourier matrix is used as the measurement matrix and the wavelet transform is usually used as sparsifying transform matrix. However, the incoherence between the randomly under-sampled Fourier matrix and the wavelet matrix is not optimal, which can deteriorate the performance of CS-MRI. Using the mathematical result that noiselets are maximally incoherent with wavelets, this paper introduces the noiselet unitary bases as the measurement matrix to improve the incoherence and RIP in CS-MRI. Based on an empirical RIP analysis that compares the multichannel noiselet and multichannel Fourier measurement matrices in CS-MRI, we propose a multichannel compressive sensing (MCS) framework to take the advantage of multichannel data acquisition used in MRI scanners. Simulations are presented in the MCS framework to compare the performance of noiselet encoding reconstructions and Fourier encoding reconstructions at different acceleration factors. The comparisons indicate that multichannel noiselet measurement matrix has better RIP than that of its Fourier counterpart, and that noiselet encoded MCS-MRI outperforms Fourier encoded MCS-MRI in preserving image resolution and can achieve higher acceleration factors. To demonstrate the feasibility of the proposed noiselet encoding scheme, a pulse sequences with tailored spatially selective RF excitation pulses was designed and implemented on a 3T scanner to acquire the data in the noiselet domain from a phantom and a human brain. The results indicate that noislet encoding preserves image resolution better than Fouirer encoding. PMID:25965548

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

PubMed

Yang, Li; Wang, Guobao; Qi, Jinyi

2016-04-01

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.

Radial k-t SPIRiT: autocalibrated parallel imaging for generalized phase-contrast MRI.

PubMed

Santelli, Claudio; Schaeffter, Tobias; Kozerke, Sebastian

2014-11-01

To extend SPIRiT to additionally exploit temporal correlations for highly accelerated generalized phase-contrast MRI and to compare the performance of the proposed radial k-t SPIRiT method relative to frame-by-frame SPIRiT and radial k-t GRAPPA reconstruction for velocity and turbulence mapping in the aortic arch. Free-breathing navigator-gated two-dimensional radial cine imaging with three-directional multi-point velocity encoding was implemented and fully sampled data were obtained in the aortic arch of healthy volunteers. Velocities were encoded with three different first gradient moments per axis to permit quantification of mean velocity and turbulent kinetic energy. Velocity and turbulent kinetic energy maps from up to 14-fold undersampled data were compared for k-t SPIRiT, frame-by-frame SPIRiT, and k-t GRAPPA relative to the fully sampled reference. Using k-t SPIRiT, improvements in magnitude and velocity reconstruction accuracy were found. Temporally resolved magnitude profiles revealed a reduction in spatial blurring with k-t SPIRiT compared with frame-by-frame SPIRiT and k-t GRAPPA for all velocity encodings, leading to improved estimates of turbulent kinetic energy. k-t SPIRiT offers improved reconstruction accuracy at high radial undersampling factors and hence facilitates the use of generalized phase-contrast MRI for routine use. Copyright © 2013 Wiley Periodicals, Inc.

A fast and flexible MRI system for the study of dynamic vocal tract shaping.

PubMed

Lingala, Sajan Goud; Zhu, Yinghua; Kim, Yoon-Chul; Toutios, Asterios; Narayanan, Shrikanth; Nayak, Krishna S

2017-01-01

The aim of this work was to develop and evaluate an MRI-based system for study of dynamic vocal tract shaping during speech production, which provides high spatial and temporal resolution. The proposed system utilizes (a) custom eight-channel upper airway coils that have high sensitivity to upper airway regions of interest, (b) two-dimensional golden angle spiral gradient echo acquisition, (c) on-the-fly view-sharing reconstruction, and (d) off-line temporal finite difference constrained reconstruction. The system also provides simultaneous noise-cancelled and temporally aligned audio. The system is evaluated in 3 healthy volunteers, and 1 tongue cancer patient, with a broad range of speech tasks. We report spatiotemporal resolutions of 2.4 × 2.4 mm 2 every 12 ms for single-slice imaging, and 2.4 × 2.4 mm 2 every 36 ms for three-slice imaging, which reflects roughly 7-fold acceleration over Nyquist sampling. This system demonstrates improved temporal fidelity in capturing rapid vocal tract shaping for tasks, such as producing consonant clusters in speech, and beat-boxing sounds. Novel acoustic-articulatory analysis was also demonstrated. A synergistic combination of custom coils, spiral acquisitions, and constrained reconstruction enables visualization of rapid speech with high spatiotemporal resolution in multiple planes. Magn Reson Med 77:112-125, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dedicated magnetic resonance imaging in the radiotherapy clinic.

PubMed

Karlsson, Mikael; Karlsson, Magnus G; Nyholm, Tufve; Amies, Christopher; Zackrisson, Björn

2009-06-01

To introduce a novel technology arrangement in an integrated environment and outline the logistics model needed to incorporate dedicated magnetic resonance (MR) imaging in the radiotherapy workflow. An initial attempt was made to analyze the value and feasibility of MR-only imaging compared to computed tomography (CT) imaging, testing the assumption that MR is a better choice for target and healthy tissue delineation in radiotherapy. A 1.5-T MR unit with a 70-cm-bore size was installed close to a linear accelerator, and a special trolley was developed for transporting patients who were fixated in advance between the MR unit and the accelerator. New MR-based workflow procedures were developed and evaluated. MR-only treatment planning has been facilitated, thus avoiding all registration errors between CT and MR scans, but several new aspects of MR imaging must be considered. Electron density information must be obtained by other methods. Generation of digitally reconstructed radiographs (DRR) for x-ray setup verification is not straight forward, and reliable corrections of geometrical distortions must be applied. The feasibility of MR imaging virtual simulation has been demonstrated, but a key challenge to overcome is correct determination of the skeleton, which is often needed for the traditional approach of beam modeling. The trolley solution allows for a highly precise setup for soft tissue tumors without the invasive handling of radiopaque markers. The new logistics model with an integrated MR unit is efficient and will allow for improved tumor definition and geometrical precision without a significant loss of dosimetric accuracy. The most significant development needed is improved bone imaging.

A new perspective on global mean sea level (GMSL) acceleration

NASA Astrophysics Data System (ADS)

Watson, Phil J.

2016-06-01

The vast body of contemporary climate change science is largely underpinned by the premise of a measured acceleration from anthropogenic forcings evident in key climate change proxies -- greenhouse gas emissions, temperature, and mean sea level. By virtue, over recent years, the issue of whether or not there is a measurable acceleration in global mean sea level has resulted in fierce, widespread professional, social, and political debate. Attempts to measure acceleration in global mean sea level (GMSL) have often used comparatively crude analysis techniques providing little temporal instruction on these key questions. This work proposes improved techniques to measure real-time velocity and acceleration based on five GMSL reconstructions spanning the time frame from 1807 to 2014 with substantially improved temporal resolution. While this analysis highlights key differences between the respective reconstructions, there is now more robust, convincing evidence of recent acceleration in the trend of GMSL.

Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

NASA Astrophysics Data System (ADS)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

Combined reconstruction of the anterior cruciate ligament associated with anterolateral tenodesis effectively controls the acceleration of the tibia during the pivot shift.

PubMed

Hardy, Alexandre; Casabianca, Laurent; Hardy, Edouard; Grimaud, Olivier; Meyer, Alain

2017-04-01

The pivot shift test is quantified subjectively during assessment of patients presenting with suspected Anterior Cruciate Ligament (ACL) tears and has a low interobserver reproducibility. The Kinematic Rapid Assessment (KiRA) is a triaxial accelerometer that makes it possible to non-invasively quantify tibial acceleration during the pivot shift test. Abolishing pivot shift is considered to be a key element in surgical reconstruction but is incomplete in 25-38% of patients. Patients were included prospectively. Inclusion criteria were patients requiring ACL reconstruction associated with at least one of the following factors corresponding to the patient who have a high risk of rupture either by their sports activity, a failure case, or the notion of important rotational laxity: the patient practiced a competitive pivot-contact sport, revision ACL reconstruction (besides STG (semitendinosus-gracilis graft) repair), subjective explosive rotational laxity, Segond fracture, and TELOS value of >10 mm. Standardized pre- and postoperative pivot shift tests were immediately performed under anesthesia in both knees. Forty-three patients were included. Mean preoperative variations in tibial acceleration in the healthy and injured knees were 1.2 ± 0.1 and 2.7 ± 0.3 m/s 2 , respectively, p < 0.01. A statistically significant decrease in immediate postoperative mean variations in acceleration in the injured knee occurred: 1.5 ± 0.3 m/s 2 , p < 0.01. There was no longer any statistical difference between postoperative contralateral healthy knees and operated knees (n.s). Combined ACL reconstruction associated with anterolateral tenodesis suppress acute pathologic tibial acceleration in the pivot shift. III.

Optshrink LR + S: accelerated fMRI reconstruction using non-convex optimal singular value shrinkage.

PubMed

Aggarwal, Priya; Shrivastava, Parth; Kabra, Tanay; Gupta, Anubha

2017-03-01

This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l 1 minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.

Penalized maximum likelihood reconstruction for x-ray differential phase-contrast tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brendel, Bernhard, E-mail: bernhard.brendel@philips.com; Teuffenbach, Maximilian von; Noël, Peter B.

2016-01-15

Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods: We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penaltymore » comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts.« less

Investigation of optimization-based reconstruction with an image-total-variation constraint in PET

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Ye, Jinghan; Chen, Buxin; Perkins, Amy E.; Rose, Sean; Sidky, Emil Y.; Kao, Chien-Min; Xia, Dan; Tung, Chi-Hua; Pan, Xiaochuan

2016-08-01

Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

New Insights on Subsurface Imaging of Carbon Nanotubes in Polymer Composites via Scanning Electron Microscopy

NASA Technical Reports Server (NTRS)

Zhao, Minhua; Ming, Bin; Kim, Jae-Woo; Gibbons, Luke J.; Gu, Xiaohong; Nguyen, Tinh; Park, Cheol; Lillehei, Peter T.; Villarrubia, J. S.; Vladar, Andras E.;

A neural network approach for image reconstruction in electron magnetic resonance tomography.

PubMed

Durairaj, D Christopher; Krishna, Murali C; Murugesan, Ramachandran

2007-10-01

An object-oriented, artificial neural network (ANN) based, application system for reconstruction of two-dimensional spatial images in electron magnetic resonance (EMR) tomography is presented. The standard back propagation algorithm is utilized to train a three-layer sigmoidal feed-forward, supervised, ANN to perform the image reconstruction. The network learns the relationship between the 'ideal' images that are reconstructed using filtered back projection (FBP) technique and the corresponding projection data (sinograms). The input layer of the network is provided with a training set that contains projection data from various phantoms as well as in vivo objects, acquired from an EMR imager. Twenty five different network configurations are investigated to test the ability of the generalization of the network. The trained ANN then reconstructs two-dimensional temporal spatial images that present the distribution of free radicals in biological systems. Image reconstruction by the trained neural network shows better time complexity than the conventional iterative reconstruction algorithms such as multiplicative algebraic reconstruction technique (MART). The network is further explored for image reconstruction from 'noisy' EMR data and the results show better performance than the FBP method. The network is also tested for its ability to reconstruct from limited-angle EMR data set.

An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

PubMed

Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values.

GPU-based prompt gamma ray imaging from boron neutron capture therapy.

PubMed

Yoon, Do-Kun; Jung, Joo-Young; Jo Hong, Key; Sil Lee, Keum; Suk Suh, Tae

2015-01-01

The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU). Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray image reconstruction using the GPU computation for BNCT simulations.

An Object-Oriented Simulator for 3D Digital Breast Tomosynthesis Imaging System

PubMed Central

Cengiz, Kubra

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

Image reconstruction: an overview for clinicians.

PubMed

Hansen, Michael S; Kellman, Peter

2015-03-01

Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI). The MRI raw data is not acquired in image space and the role of the image reconstruction process is to transform the acquired raw data into images that can be interpreted clinically. This process involves multiple signal processing steps that each have an impact on the image quality. This review explains the basic terminology used for describing and quantifying image quality in terms of signal-to-noise ratio and point spread function. In this context, several commonly used image reconstruction components are discussed. The image reconstruction components covered include noise prewhitening for phased array data acquisition, interpolation needed to reconstruct square pixels, raw data filtering for reducing Gibbs ringing artifacts, Fourier transforms connecting the raw data with image space, and phased array coil combination. The treatment of phased array coils includes a general explanation of parallel imaging as a coil combination technique. The review is aimed at readers with no signal processing experience and should enable them to understand what role basic image reconstruction steps play in the formation of clinical images and how the resulting image quality is described. © 2014 Wiley Periodicals, Inc.

Iterative image reconstruction for PROPELLER-MRI using the nonuniform fast fourier transform.

PubMed

Tamhane, Ashish A; Anastasio, Mark A; Gui, Minzhi; Arfanakis, Konstantinos

2010-07-01

To investigate an iterative image reconstruction algorithm using the nonuniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI. Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it with that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased signal to noise ratio, reduced artifacts, for similar spatial resolution, compared with gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter, the new reconstruction technique may provide PROPELLER images with improved image quality compared with conventional gridding. (c) 2010 Wiley-Liss, Inc.

Iterative Image Reconstruction for PROPELLER-MRI using the NonUniform Fast Fourier Transform

PubMed Central

Tamhane, Ashish A.; Anastasio, Mark A.; Gui, Minzhi; Arfanakis, Konstantinos

2013-01-01

Purpose To investigate an iterative image reconstruction algorithm using the non-uniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping parallEL Lines with Enhanced Reconstruction) MRI. Materials and Methods Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it to that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. Results It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased SNR, reduced artifacts, for similar spatial resolution, compared to gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. Conclusion An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter the new reconstruction technique may provide PROPELLER images with improved image quality compared to conventional gridding. PMID:20578028

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

PubMed Central

Wang, Kun; Su, Richard; Oraevsky, Alexander A; Anastasio, Mark A

2012-01-01

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications. PMID:22864062

A high-level 3D visualization API for Java and ImageJ.

PubMed

Schmid, Benjamin; Schindelin, Johannes; Cardona, Albert; Longair, Mark; Heisenberg, Martin

2010-05-21

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

NASA Astrophysics Data System (ADS)

Melli, S. Ali; Wahid, Khan A.; Babyn, Paul; Cooper, David M. L.; Gopi, Varun P.

2016-12-01

Synchrotron X-ray Micro Computed Tomography (Micro-CT) is an imaging technique which is increasingly used for non-invasive in vivo preclinical imaging. However, it often requires a large number of projections from many different angles to reconstruct high-quality images leading to significantly high radiation doses and long scan times. To utilize this imaging technique further for in vivo imaging, we need to design reconstruction algorithms that reduce the radiation dose and scan time without reduction of reconstructed image quality. This research is focused on using a combination of gradient-based Douglas-Rachford splitting and discrete wavelet packet shrinkage image denoising methods to design an algorithm for reconstruction of large-scale reduced-view synchrotron Micro-CT images with acceptable quality metrics. These quality metrics are computed by comparing the reconstructed images with a high-dose reference image reconstructed from 1800 equally spaced projections spanning 180°. Visual and quantitative-based performance assessment of a synthetic head phantom and a femoral cortical bone sample imaged in the biomedical imaging and therapy bending magnet beamline at the Canadian Light Source demonstrates that the proposed algorithm is superior to the existing reconstruction algorithms. Using the proposed reconstruction algorithm to reduce the number of projections in synchrotron Micro-CT is an effective way to reduce the overall radiation dose and scan time which improves in vivo imaging protocols.

Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non-EPI fMRI at 9.4T

PubMed Central

Kim, Seong-Gi; Ye, Jong Chul

2015-01-01

Conventional functional magnetic resonance imaging (fMRI) technique known as gradient-recalled echo (GRE) echo-planar imaging (EPI) is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP) have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS). In this study, we tested the feasibility of k-t FOCUSS—one of the high performance CS algorithms for dynamic MRI—for non-EPI fMRI at 9.4T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns and k-t FOCUSS variations were investigated. Experimental results show that an optimized k-t FOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields. PMID:26413503

Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision

PubMed Central

Wang, Yaming; Tong, Lingling; Jiang, Mingfeng; Zheng, Junbao

2015-01-01

In this paper, the problem of non-rigid structure estimation in trajectory space from monocular vision is investigated. Similar to the Point Trajectory Approach (PTA), based on characteristic points’ trajectories described by a predefined Discrete Cosine Transform (DCT) basis, the structure matrix was also calculated by using a factorization method. To further optimize the non-rigid structure estimation from monocular vision, the rank minimization problem about structure matrix is proposed to implement the non-rigid structure estimation by introducing the basic low-rank condition. Moreover, the Accelerated Proximal Gradient (APG) algorithm is proposed to solve the rank minimization problem, and the initial structure matrix calculated by the PTA method is optimized. The APG algorithm can converge to efficient solutions quickly and lessen the reconstruction error obviously. The reconstruction results of real image sequences indicate that the proposed approach runs reliably, and effectively improves the accuracy of non-rigid structure estimation from monocular vision. PMID:26473863

Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel.

PubMed

Zhou, Qijing; Jiang, Biao; Dong, Fei; Huang, Peiyu; Liu, Hongtao; Zhang, Minming

2014-01-01

To evaluate the improvement of iterative reconstruction in image space (IRIS) technique in computed tomographic (CT) coronary stent imaging with sharp kernel, and to make a trade-off analysis. Fifty-six patients with 105 stents were examined by 128-slice dual-source CT coronary angiography (CTCA). Images were reconstructed using standard filtered back projection (FBP) and IRIS with both medium kernel and sharp kernel applied. Image noise and the stent diameter were investigated. Image noise was measured both in background vessel and in-stent lumen as objective image evaluation. Image noise score and stent score were performed as subjective image evaluation. The CTCA images reconstructed with IRIS were associated with significant noise reduction compared to that of CTCA images reconstructed using FBP technique in both of background vessel and in-stent lumen (the background noise decreased by approximately 25.4% ± 8.2% in medium kernel (P

SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niemkiewicz, J; Palmiotti, A; Miner, M

2014-06-01

Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU valuesmore » were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation treatment planning accuracy.« less

A novel data processing technique for image reconstruction of penumbral imaging

NASA Astrophysics Data System (ADS)

Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

2011-06-01

CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

Ultra-low-dose computed tomographic angiography with model-based iterative reconstruction compared with standard-dose imaging after endovascular aneurysm repair: a prospective pilot study.

PubMed

Naidu, Sailen G; Kriegshauser, J Scott; Paden, Robert G; He, Miao; Wu, Qing; Hara, Amy K

2014-12-01

An ultra-low-dose radiation protocol reconstructed with model-based iterative reconstruction was compared with our standard-dose protocol. This prospective study evaluated 20 men undergoing surveillance-enhanced computed tomography after endovascular aneurysm repair. All patients underwent standard-dose and ultra-low-dose venous phase imaging; images were compared after reconstruction with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Objective measures of aortic contrast attenuation and image noise were averaged. Images were subjectively assessed (1 = worst, 5 = best) for diagnostic confidence, image noise, and vessel sharpness. Aneurysm sac diameter and endoleak detection were compared. Quantitative image noise was 26% less with ultra-low-dose model-based iterative reconstruction than with standard-dose adaptive statistical iterative reconstruction and 58% less than with ultra-low-dose adaptive statistical iterative reconstruction. Average subjective noise scores were not different between ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction (3.8 vs. 4.0, P = .25). Subjective scores for diagnostic confidence were better with standard-dose adaptive statistical iterative reconstruction than with ultra-low-dose model-based iterative reconstruction (4.4 vs. 4.0, P = .002). Vessel sharpness was decreased with ultra-low-dose model-based iterative reconstruction compared with standard-dose adaptive statistical iterative reconstruction (3.3 vs. 4.1, P < .0001). Ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction aneurysm sac diameters were not significantly different (4.9 vs. 4.9 cm); concordance for the presence of endoleak was 100% (P < .001). Compared with a standard-dose technique, an ultra-low-dose model-based iterative reconstruction protocol provides comparable image quality and diagnostic assessment at a 73% lower radiation dose.

Wave optics theory and 3-D deconvolution for the light field microscope

PubMed Central

Broxton, Michael; Grosenick, Logan; Yang, Samuel; Cohen, Noy; Andalman, Aaron; Deisseroth, Karl; Levoy, Marc

2013-01-01

Light field microscopy is a new technique for high-speed volumetric imaging of weakly scattering or fluorescent specimens. It employs an array of microlenses to trade off spatial resolution against angular resolution, thereby allowing a 4-D light field to be captured using a single photographic exposure without the need for scanning. The recorded light field can then be used to computationally reconstruct a full volume. In this paper, we present an optical model for light field microscopy based on wave optics, instead of previously reported ray optics models. We also present a 3-D deconvolution method for light field microscopy that is able to reconstruct volumes at higher spatial resolution, and with better optical sectioning, than previously reported. To accomplish this, we take advantage of the dense spatio-angular sampling provided by a microlens array at axial positions away from the native object plane. This dense sampling permits us to decode aliasing present in the light field to reconstruct high-frequency information. We formulate our method as an inverse problem for reconstructing the 3-D volume, which we solve using a GPU-accelerated iterative algorithm. Theoretical limits on the depth-dependent lateral resolution of the reconstructed volumes are derived. We show that these limits are in good agreement with experimental results on a standard USAF 1951 resolution target. Finally, we present 3-D reconstructions of pollen grains that demonstrate the improvements in fidelity made possible by our method. PMID:24150383

Optimization-Based Image Reconstruction with Artifact Reduction in C-Arm CBCT

PubMed Central

Xia, Dan; Langan, David A.; Solomon, Stephen B.; Zhang, Zheng; Chen, Buxin; Lai, Hao; Sidky, Emil Y.; Pan, Xiaochuan

2016-01-01

We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g., data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility. PMID:27694700

Optimization-based image reconstruction with artifact reduction in C-arm CBCT

NASA Astrophysics Data System (ADS)

Xia, Dan; Langan, David A.; Solomon, Stephen B.; Zhang, Zheng; Chen, Buxin; Lai, Hao; Sidky, Emil Y.; Pan, Xiaochuan

2016-10-01

We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g. data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility.

[Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images].

PubMed

Zhang, Dongxia; Gan, Yangzhou; Xiong, Jing; Xia, Zeyang

2017-02-01

Complete three-dimensional(3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography(CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete3 D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.

A feasibility study for compressed sensing combined phase contrast MR angiography reconstruction

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo; Han, Bong-Soo

2012-02-01

Phase contrast magnetic resonance angiography (PC MRA) is a technique for flow velocity measurement and vessels visualization, simultaneously. The PC MRA takes long scan time because each flow encoding gradients which are composed bipolar gradient type need to reconstruct the angiography image. Moreover, it takes more image acquisition time when we use the PC MRA at the low-tesla MRI system. In this study, we studied and evaluation of feasibility for CS MRI reconstruction combined PC MRA which data acquired by low-tesla MRI system. We used non-linear reconstruction algorithm which named Bregman iteration for CS image reconstruction and validate the usefulness of CS combined PC MRA reconstruction technique. The results of CS reconstructed PC MRA images provide similar level of image quality between fully sampled reconstruction data and sparse sampled reconstruction using CS technique. Although our results used half of sampling ratio and do not used specification hardware device or performance which are improving the temporal resolution of MR image acquisition such as parallel imaging reconstruction using phased array coil or non-cartesian trajectory, we think that CS combined PC MRA technique will be helpful to increase the temporal resolution and at low-tesla MRI system.

Development and evaluation of a LOR-based image reconstruction with 3D system response modeling for a PET insert with dual-layer offset crystal design.

PubMed

Zhang, Xuezhu; Stortz, Greg; Sossi, Vesna; Thompson, Christopher J; Retière, Fabrice; Kozlowski, Piotr; Thiessen, Jonathan D; Goertzen, Andrew L

2013-12-07

In this study we present a method of 3D system response calculation for analytical computer simulation and statistical image reconstruction for a magnetic resonance imaging (MRI) compatible positron emission tomography (PET) insert system that uses a dual-layer offset (DLO) crystal design. The general analytical system response functions (SRFs) for detector geometric and inter-crystal penetration of coincident crystal pairs are derived first. We implemented a 3D ray-tracing algorithm with 4π sampling for calculating the SRFs of coincident pairs of individual DLO crystals. The determination of which detector blocks are intersected by a gamma ray is made by calculating the intersection of the ray with virtual cylinders with radii just inside the inner surface and just outside the outer-edge of each crystal layer of the detector ring. For efficient ray-tracing computation, the detector block and ray to be traced are then rotated so that the crystals are aligned along the X-axis, facilitating calculation of ray/crystal boundary intersection points. This algorithm can be applied to any system geometry using either single-layer (SL) or multi-layer array design with or without offset crystals. For effective data organization, a direct lines of response (LOR)-based indexed histogram-mode method is also presented in this work. SRF calculation is performed on-the-fly in both forward and back projection procedures during each iteration of image reconstruction, with acceleration through use of eight-fold geometric symmetry and multi-threaded parallel computation. To validate the proposed methods, we performed a series of analytical and Monte Carlo computer simulations for different system geometry and detector designs. The full-width-at-half-maximum of the numerical SRFs in both radial and tangential directions are calculated and compared for various system designs. By inspecting the sinograms obtained for different detector geometries, it can be seen that the DLO crystal design can provide better sampling density than SL or dual-layer no-offset system designs with the same total crystal length. The results of the image reconstruction with SRFs modeling for phantom studies exhibit promising image recovery capability for crystal widths of 1.27-1.43 mm and top/bottom layer lengths of 4/6 mm. In conclusion, we have developed efficient algorithms for system response modeling of our proposed PET insert with DLO crystal arrays. This provides an effective method for both 3D computer simulation and quantitative image reconstruction, and will aid in the optimization of our PET insert system with various crystal designs.

Accelerated echo-planar J-resolved spectroscopic imaging in the human brain using compressed sensing: a pilot validation in obstructive sleep apnea.

PubMed

Sarma, M K; Nagarajan, R; Macey, P M; Kumar, R; Villablanca, J P; Furuyama, J; Thomas, M A

2014-06-01

Echo-planar J-resolved spectroscopic imaging is a fast spectroscopic technique to record the biochemical information in multiple regions of the brain, but for clinical applications, time is still a constraint. Investigations of neural injury in obstructive sleep apnea have revealed structural changes in the brain, but determining the neurochemical changes requires more detailed measurements across multiple brain regions, demonstrating a need for faster echo-planar J-resolved spectroscopic imaging. Hence, we have extended the compressed sensing reconstruction of prospectively undersampled 4D echo-planar J-resolved spectroscopic imaging to investigate metabolic changes in multiple brain locations of patients with obstructive sleep apnea and healthy controls. Nonuniform undersampling was imposed along 1 spatial and 1 spectral dimension of 4D echo-planar J-resolved spectroscopic imaging, and test-retest reliability of the compressed sensing reconstruction of the nonuniform undersampling data was tested by using a brain phantom. In addition, 9 patients with obstructive sleep apnea and 11 healthy controls were investigated by using a 3T MR imaging/MR spectroscopy scanner. Significantly reduced metabolite differences were observed between patients with obstructive sleep apnea and healthy controls in multiple brain regions: NAA/Cr in the left hippocampus; total Cho/Cr and Glx/Cr in the right hippocampus; total NAA/Cr, taurine/Cr, scyllo-Inositol/Cr, phosphocholine/Cr, and total Cho/Cr in the occipital gray matter; total NAA/Cr and NAA/Cr in the medial frontal white matter; and taurine/Cr and total Cho/Cr in the left frontal white matter regions. The 4D echo-planar J-resolved spectroscopic imaging technique using the nonuniform undersampling-based acquisition and compressed sensing reconstruction in patients with obstructive sleep apnea and healthy brain is feasible in a clinically suitable time. In addition to brain metabolite changes previously reported by 1D MR spectroscopy, our results show changes of additional metabolites in patients with obstructive sleep apnea compared with healthy controls. © 2014 by American Journal of Neuroradiology.

GPU-based prompt gamma ray imaging from boron neutron capture therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Do-Kun; Jung, Joo-Young; Suk Suh, Tae, E-mail: suhsanta@catholic.ac.kr

Purpose: The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. Methods: To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU).more » Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. Results: The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). Conclusions: The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray image reconstruction using the GPU computation for BNCT simulations.« less

A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

PubMed

Konkle, Justin J; Goodwill, Patrick W; Hensley, Daniel W; Orendorff, Ryan D; Lustig, Michael; Conolly, Steven M

2015-01-01

Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

General rigid motion correction for computed tomography imaging based on locally linear embedding

NASA Astrophysics Data System (ADS)

Chen, Mianyi; He, Peng; Feng, Peng; Liu, Baodong; Yang, Qingsong; Wei, Biao; Wang, Ge

2018-02-01

The patient motion can damage the quality of computed tomography images, which are typically acquired in cone-beam geometry. The rigid patient motion is characterized by six geometric parameters and are more challenging to correct than in fan-beam geometry. We extend our previous rigid patient motion correction method based on the principle of locally linear embedding (LLE) from fan-beam to cone-beam geometry and accelerate the computational procedure with the graphics processing unit (GPU)-based all scale tomographic reconstruction Antwerp toolbox. The major merit of our method is that we need neither fiducial markers nor motion-tracking devices. The numerical and experimental studies show that the LLE-based patient motion correction is capable of calibrating the six parameters of the patient motion simultaneously, reducing patient motion artifacts significantly.

Information recovery in propagation-based imaging with decoherence effects

NASA Astrophysics Data System (ADS)

Froese, Heinrich; Lötgering, Lars; Wilhein, Thomas

2017-05-01

During the past decades the optical imaging community witnessed a rapid emergence of novel imaging modalities such as coherent diffraction imaging (CDI), propagation-based imaging and ptychography. These methods have been demonstrated to recover complex-valued scalar wave fields from redundant data without the need for refractive or diffractive optical elements. This renders these techniques suitable for imaging experiments with EUV and x-ray radiation, where the use of lenses is complicated by fabrication, photon efficiency and cost. However, decoherence effects can have detrimental effects on the reconstruction quality of the numerical algorithms involved. Here we demonstrate propagation-based optical phase retrieval from multiple near-field intensities with decoherence effects such as partially coherent illumination, detector point spread, binning and position uncertainties of the detector. Methods for overcoming these systematic experimental errors - based on the decomposition of the data into mutually incoherent modes - are proposed and numerically tested. We believe that the results presented here open up novel algorithmic methods to accelerate detector readout rates and enable subpixel resolution in propagation-based phase retrieval. Further the techniques are straightforward to be extended to methods such as CDI, ptychography and holography.

Event-by-event PET image reconstruction using list-mode origin ensembles algorithm

NASA Astrophysics Data System (ADS)

Andreyev, Andriy

2016-03-01

There is a great demand for real time or event-by-event (EBE) image reconstruction in emission tomography. Ideally, as soon as event has been detected by the acquisition electronics, it needs to be used in the image reconstruction software. This would greatly speed up the image reconstruction since most of the data will be processed and reconstructed while the patient is still undergoing the scan. Unfortunately, the current industry standard is that the reconstruction of the image would not start until all the data for the current image frame would be acquired. Implementing an EBE reconstruction for MLEM family of algorithms is possible, but not straightforward as multiple (computationally expensive) updates to the image estimate are required. In this work an alternative Origin Ensembles (OE) image reconstruction algorithm for PET imaging is converted to EBE mode and is investigated whether it is viable alternative for real-time image reconstruction. In OE algorithm all acquired events are seen as points that are located somewhere along the corresponding line-of-responses (LORs), together forming a point cloud. Iteratively, with a multitude of quasi-random shifts following the likelihood function the point cloud converges to a reflection of an actual radiotracer distribution with the degree of accuracy that is similar to MLEM. New data can be naturally added into the point cloud. Preliminary results with simulated data show little difference between regular reconstruction and EBE mode, proving the feasibility of the proposed approach.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

High-resolution reconstruction for terahertz imaging.

PubMed

Xu, Li-Min; Fan, Wen-Hui; Liu, Jia

2014-11-20

We present a high-resolution (HR) reconstruction model and algorithms for terahertz imaging, taking advantage of super-resolution methodology and algorithms. The algorithms used include projection onto a convex sets approach, iterative backprojection approach, Lucy-Richardson iteration, and 2D wavelet decomposition reconstruction. Using the first two HR reconstruction methods, we successfully obtain HR terahertz images with improved definition and lower noise from four low-resolution (LR) 22×24 terahertz images taken from our homemade THz-TDS system at the same experimental conditions with 1.0 mm pixel. Using the last two HR reconstruction methods, we transform one relatively LR terahertz image to a HR terahertz image with decreased noise. This indicates potential application of HR reconstruction methods in terahertz imaging with pulsed and continuous wave terahertz sources.

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT.

PubMed

Chen, Guang-Hong; Li, Yinsheng

2015-08-01

In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial-temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial-temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial-temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. In numerical simulations, the 240(∘) short scan angular span was divided into four consecutive 60(∘) angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200(∘), three 66(∘) angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60(∘) angular subsectors.

Analysis of the significance of the measurement of acceleration with respect to lateral laxity of the anterior cruciate ligament insufficient knee.

PubMed

Yoshimura, I; Naito, M; Hara, M; Zhang, J

2000-01-01

The purpose of this study was to assess dynamically the lateral thrust of anterior cruciate ligament (ACL) insufficient knees, and from the findings determine any relationship between ACL insufficiency and the later development of osteoarthritis (OA). We investigated 80 knees in 40 patients awaiting ACL reconstruction and 25 knees of 25 patients, which had undergone ACL reconstruction. An acceleration sensor was fixed to the anterior tibial tubercle and this 'acted' in two directions--medial lateral and perpendicular. The peak value of the lateral acceleration immediately after heel strike was significantly greater in the ACL insufficient knees when compared to their opposite normal knees. When the periods from injury were compared, the lateral thrust of the injured side after 3 years or more was significantly greater than in the first 3 years. There was no significant difference between the normal knees and the ACL reconstructed knees. The results indicated that the lateral acceleration peak value was significantly greater in the ACL insufficient knees than in their opposite normal knees.

Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation.

PubMed

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2015-12-01

This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. © 2014 Wiley Periodicals, Inc.

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

PubMed

Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

2017-08-15

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an acceleration of four and L+S reconstruction can achieve a brain coverage of 40 slices at 2mm isotropic resolution and 64 x 64 matrix size every 500ms. Copyright © 2017 Elsevier Inc. All rights reserved.

TH-A-18C-04: Ultrafast Cone-Beam CT Scatter Correction with GPU-Based Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Y; Southern Medical University, Guangzhou; Bai, T

2014-06-15

Purpose: Scatter artifacts severely degrade image quality of cone-beam CT (CBCT). We present an ultrafast scatter correction framework by using GPU-based Monte Carlo (MC) simulation and prior patient CT image, aiming at automatically finish the whole process including both scatter correction and reconstructions within 30 seconds. Methods: The method consists of six steps: 1) FDK reconstruction using raw projection data; 2) Rigid Registration of planning CT to the FDK results; 3) MC scatter calculation at sparse view angles using the planning CT; 4) Interpolation of the calculated scatter signals to other angles; 5) Removal of scatter from the raw projections;more » 6) FDK reconstruction using the scatter-corrected projections. In addition to using GPU to accelerate MC photon simulations, we also use a small number of photons and a down-sampled CT image in simulation to further reduce computation time. A novel denoising algorithm is used to eliminate MC scatter noise caused by low photon numbers. The method is validated on head-and-neck cases with simulated and clinical data. Results: We have studied impacts of photo histories, volume down sampling factors on the accuracy of scatter estimation. The Fourier analysis was conducted to show that scatter images calculated at 31 angles are sufficient to restore those at all angles with <0.1% error. For the simulated case with a resolution of 512×512×100, we simulated 10M photons per angle. The total computation time is 23.77 seconds on a Nvidia GTX Titan GPU. The scatter-induced shading/cupping artifacts are substantially reduced, and the average HU error of a region-of-interest is reduced from 75.9 to 19.0 HU. Similar results were found for a real patient case. Conclusion: A practical ultrafast MC-based CBCT scatter correction scheme is developed. The whole process of scatter correction and reconstruction is accomplished within 30 seconds. This study is supported in part by NIH (1R01CA154747-01), The Core Technology Research in Strategic Emerging Industry, Guangdong, China (2011A081402003)« less

Volume-of-interest reconstruction from severely truncated data in dental cone-beam CT

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Kusnoto, Budi; Han, Xiao; Sidky, E. Y.; Pan, Xiaochuan

2015-03-01

As cone-beam computed tomography (CBCT) has gained popularity rapidly in dental imaging applications in the past two decades, radiation dose in CBCT imaging remains a potential, health concern to the patients. It is a common practice in dental CBCT imaging that only a small volume of interest (VOI) containing the teeth of interest is illuminated, thus substantially lowering imaging radiation dose. However, this would yield data with severe truncations along both transverse and longitudinal directions. Although images within the VOI reconstructed from truncated data can be of some practical utility, they often are compromised significantly by truncation artifacts. In this work, we investigate optimization-based reconstruction algorithms for VOI image reconstruction from CBCT data of dental patients containing severe truncations. In an attempt to further reduce imaging dose, we also investigate optimization-based image reconstruction from severely truncated data collected at projection views substantially fewer than those used in clinical dental applications. Results of our study show that appropriately designed optimization-based reconstruction can yield VOI images with reduced truncation artifacts, and that, when reconstructing from only one half, or even one quarter, of clinical data, it can also produce VOI images comparable to that of clinical images.

A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT

PubMed Central

Cho, Seungryong; Xia, Dan; Pellizzari, Charles A.; Pan, Xiaochuan

2010-01-01

Purpose: Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. Methods: The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack–Noo-formula-based filteredbackprojection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. Results: The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. Conclusions: They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories. PMID:20175463

A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT.

PubMed

Cho, Seungryong; Xia, Dan; Pellizzari, Charles A; Pan, Xiaochuan

2010-01-01

Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredback-projection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

Ultrasound tomography imaging with waveform sound speed: parenchymal changes in women undergoing tamoxifen therapy

NASA Astrophysics Data System (ADS)

Sak, Mark; Duric, Neb; Littrup, Peter; Sherman, Mark; Gierach, Gretchen

2017-03-01

Ultrasound tomography (UST) is an emerging modality that can offer quantitative measurements of breast density. Recent breakthroughs in UST image reconstruction involve the use of a waveform reconstruction as opposed to a raybased reconstruction. The sound speed (SS) images that are created using the waveform reconstruction have a much higher image quality. These waveform images offer improved resolution and contrasts between regions of dense and fatty tissues. As part of a study that was designed to assess breast density changes using UST sound speed imaging among women undergoing tamoxifen therapy, UST waveform sound speed images were then reconstructed for a subset of participants. These initial results show that changes to the parenchymal tissue can more clearly be visualized when using the waveform sound speed images. Additional quantitative testing of the waveform images was also started to test the hypothesis that waveform sound speed images are a more robust measure of breast density than ray-based reconstructions. Further analysis is still needed to better understand how tamoxifen affects breast tissue.

A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

NASA Astrophysics Data System (ADS)

Wu, Wei; Zhao, Dewei; Zhang, Huan

2015-12-01

Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

Image reconstruction for PET/CT scanners: past achievements and future challenges

PubMed Central

Tong, Shan; Alessio, Adam M; Kinahan, Paul E

2011-01-01

PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831

Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

PubMed

Li, Yusheng; Matej, Samuel; Metzler, Scott D

2014-12-01

Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate that the reconstructions from super-sampled data sets using a fine system matrix yield improved image quality compared to the reconstructions using a coarse system matrix. Super-sampling reconstructions with different count levels showed that the more spatial-resolution improvement can be obtained with higher count at a larger iteration number. The authors developed a super-sampling reconstruction framework that can reconstruct super-resolution images using the super-sampling data sets simultaneously with known acquisition motion. The super-sampling PET acquisition using the proposed algorithms provides an effective and economic way to improve image quality for PET imaging, which has an important implication in preclinical and clinical region-of-interest PET imaging applications.

Study on the algorithm of computational ghost imaging based on discrete fourier transform measurement matrix

NASA Astrophysics Data System (ADS)

Zhang, Leihong; Liang, Dong; Li, Bei; Kang, Yi; Pan, Zilan; Zhang, Dawei; Gao, Xiumin; Ma, Xiuhua

2016-07-01

On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.

Wavelet-space Correlation Imaging for High-speed MRI without Motion Monitoring or Data Segmentation

PubMed Central

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2014-01-01

Purpose This study aims to 1) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and 2) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Methods Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called “wavelet-space correlation imaging”, is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Results Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Conclusion Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. PMID:25470230

Decomposed direct matrix inversion for fast non-cartesian SENSE reconstructions.

PubMed

Qian, Yongxian; Zhang, Zhenghui; Wang, Yi; Boada, Fernando E

2006-08-01

A new k-space direct matrix inversion (DMI) method is proposed here to accelerate non-Cartesian SENSE reconstructions. In this method a global k-space matrix equation is established on basic MRI principles, and the inverse of the global encoding matrix is found from a set of local matrix equations by taking advantage of the small extension of k-space coil maps. The DMI algorithm's efficiency is achieved by reloading the precalculated global inverse when the coil maps and trajectories remain unchanged, such as in dynamic studies. Phantom and human subject experiments were performed on a 1.5T scanner with a standard four-channel phased-array cardiac coil. Interleaved spiral trajectories were used to collect fully sampled and undersampled 3D raw data. The equivalence of the global k-space matrix equation to its image-space version, was verified via conjugate gradient (CG) iterative algorithms on a 2x undersampled phantom and numerical-model data sets. When applied to the 2x undersampled phantom and human-subject raw data, the decomposed DMI method produced images with small errors (< or = 3.9%) relative to the reference images obtained from the fully-sampled data, at a rate of 2 s per slice (excluding 4 min for precalculating the global inverse at an image size of 256 x 256). The DMI method may be useful for noise evaluations in parallel coil designs, dynamic MRI, and 3D sodium MRI with fixed coils and trajectories. Copyright 2006 Wiley-Liss, Inc.

Super resolution reconstruction of infrared images based on classified dictionary learning

NASA Astrophysics Data System (ADS)

Liu, Fei; Han, Pingli; Wang, Yi; Li, Xuan; Bai, Lu; Shao, Xiaopeng

2018-05-01

Infrared images always suffer from low-resolution problems resulting from limitations of imaging devices. An economical approach to combat this problem involves reconstructing high-resolution images by reasonable methods without updating devices. Inspired by compressed sensing theory, this study presents and demonstrates a Classified Dictionary Learning method to reconstruct high-resolution infrared images. It classifies features of the samples into several reasonable clusters and trained a dictionary pair for each cluster. The optimal pair of dictionaries is chosen for each image reconstruction and therefore, more satisfactory results is achieved without the increase in computational complexity and time cost. Experiments and results demonstrated that it is a viable method for infrared images reconstruction since it improves image resolution and recovers detailed information of targets.

TU-FG-BRB-07: GPU-Based Prompt Gamma Ray Imaging From Boron Neutron Capture Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, S; Suh, T; Yoon, D

Purpose: The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. Methods: To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU).more » Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. Results: The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). Conclusion: The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray reconstruction using the GPU computation for BNCT simulations.« less

Incomplete projection reconstruction of computed tomography based on the modified discrete algebraic reconstruction technique

NASA Astrophysics Data System (ADS)

Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei

2018-02-01

Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.

The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

PubMed

Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

2014-06-01

Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

NVIDIA OptiX ray-tracing engine as a new tool for modelling medical imaging systems

NASA Astrophysics Data System (ADS)

Pietrzak, Jakub; Kacperski, Krzysztof; Cieślar, Marek

2015-03-01

The most accurate technique to model the X- and gamma radiation path through a numerically defined object is the Monte Carlo simulation which follows single photons according to their interaction probabilities. A simplified and much faster approach, which just integrates total interaction probabilities along selected paths, is known as ray tracing. Both techniques are used in medical imaging for simulating real imaging systems and as projectors required in iterative tomographic reconstruction algorithms. These approaches are ready for massive parallel implementation e.g. on Graphics Processing Units (GPU), which can greatly accelerate the computation time at a relatively low cost. In this paper we describe the application of the NVIDIA OptiX ray-tracing engine, popular in professional graphics and rendering applications, as a new powerful tool for X- and gamma ray-tracing in medical imaging. It allows the implementation of a variety of physical interactions of rays with pixel-, mesh- or nurbs-based objects, and recording any required quantities, like path integrals, interaction sites, deposited energies, and others. Using the OptiX engine we have implemented a code for rapid Monte Carlo simulations of Single Photon Emission Computed Tomography (SPECT) imaging, as well as the ray-tracing projector, which can be used in reconstruction algorithms. The engine generates efficient, scalable and optimized GPU code, ready to run on multi GPU heterogeneous systems. We have compared the results our simulations with the GATE package. With the OptiX engine the computation time of a Monte Carlo simulation can be reduced from days to minutes.

Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

PubMed

Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

2018-06-01

Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

Evaluation of the Intel Xeon Phi Co-processor to accelerate the sensitivity map calculation for PET imaging

NASA Astrophysics Data System (ADS)

Dey, T.; Rodrigue, P.

2015-07-01

We aim to evaluate the Intel Xeon Phi coprocessor for acceleration of 3D Positron Emission Tomography (PET) image reconstruction. We focus on the sensitivity map calculation as one computational intensive part of PET image reconstruction, since it is a promising candidate for acceleration with the Many Integrated Core (MIC) architecture of the Xeon Phi. The computation of the voxels in the field of view (FoV) can be done in parallel and the 103 to 104 samples needed to calculate the detection probability of each voxel can take advantage of vectorization. We use the ray tracing kernels of the Embree project to calculate the hit points of the sample rays with the detector and in a second step the sum of the radiological path taking into account attenuation is determined. The core components are implemented using the Intel single instruction multiple data compiler (ISPC) to enable a portable implementation showing efficient vectorization either on the Xeon Phi and the Host platform. On the Xeon Phi, the calculation of the radiological path is also implemented in hardware specific intrinsic instructions (so-called `intrinsics') to allow manually-optimized vectorization. For parallelization either OpenMP and ISPC tasking (based on pthreads) are evaluated.Our implementation achieved a scalability factor of 0.90 on the Xeon Phi coprocessor (model 5110P) with 60 cores at 1 GHz. Only minor differences were found between parallelization with OpenMP and the ISPC tasking feature. The implementation using intrinsics was found to be about 12% faster than the portable ISPC version. With this version, a speedup of 1.43 was achieved on the Xeon Phi coprocessor compared to the host system (HP SL250s Gen8) equipped with two Xeon (E5-2670) CPUs, with 8 cores at 2.6 to 3.3 GHz each. Using a second Xeon Phi card the speedup could be further increased to 2.77. No significant differences were found between the results of the different Xeon Phi and the Host implementations. The examination showed that a reasonable speedup of sensitivity map calculation could be achieved on the Xeon Phi either by a portable or a hardware specific implementation.

Influence of the Pixel Sizes of Reference Computed Tomography on Single-photon Emission Computed Tomography Image Reconstruction Using Conjugate-gradient Algorithm.

PubMed

Okuda, Kyohei; Sakimoto, Shota; Fujii, Susumu; Ida, Tomonobu; Moriyama, Shigeru

The frame-of-reference using computed-tomography (CT) coordinate system on single-photon emission computed tomography (SPECT) reconstruction is one of the advanced characteristics of the xSPECT reconstruction system. The aim of this study was to reveal the influence of the high-resolution frame-of-reference on the xSPECT reconstruction. 99m Tc line-source phantom and National Electrical Manufacturers Association (NEMA) image quality phantom were scanned using the SPECT/CT system. xSPECT reconstructions were performed with the reference CT images in different sizes of the display field-of-view (DFOV) and pixel. The pixel sizes of the reconstructed xSPECT images were close to 2.4 mm, which is acquired as originally projection data, even if the reference CT resolution was varied. The full width at half maximum (FWHM) of the line-source, absolute recovery coefficient, and background variability of image quality phantom were independent on the sizes of DFOV in the reference CT images. The results of this study revealed that the image quality of the reconstructed xSPECT images is not influenced by the resolution of frame-of-reference on SPECT reconstruction.

A Dictionary Learning Approach with Overlap for the Low Dose Computed Tomography Reconstruction and Its Vectorial Application to Differential Phase Tomography

PubMed Central

Mirone, Alessandro; Brun, Emmanuel; Coan, Paola

2014-01-01

X-ray based Phase-Contrast Imaging (PCI) techniques have been demonstrated to enhance the visualization of soft tissues in comparison to conventional imaging methods. Nevertheless the delivered dose as reported in the literature of biomedical PCI applications often equals or exceeds the limits prescribed in clinical diagnostics. The optimization of new computed tomography strategies which include the development and implementation of advanced image reconstruction procedures is thus a key aspect. In this scenario, we implemented a dictionary learning method with a new form of convex functional. This functional contains in addition to the usual sparsity inducing and fidelity terms, a new term which forces similarity between overlapping patches in the superimposed regions. The functional depends on two free regularization parameters: a coefficient multiplying the sparsity-inducing norm of the patch basis functions coefficients, and a coefficient multiplying the norm of the differences between patches in the overlapping regions. The solution is found by applying the iterative proximal gradient descent method with FISTA acceleration. The gradient is computed by calculating projection of the solution and its error backprojection at each iterative step. We study the quality of the solution, as a function of the regularization parameters and noise, on synthetic data for which the solution is a-priori known. We apply the method on experimental data in the case of Differential Phase Tomography. For this case we use an original approach which consists in using vectorial patches, each patch having two components: one per each gradient component. The resulting algorithm, implemented in the European Synchrotron Radiation Facility tomography reconstruction code PyHST, has proven to be efficient and well-adapted to strongly reduce the required dose and the number of projections in medical tomography. PMID:25531987

A dictionary learning approach with overlap for the low dose computed tomography reconstruction and its vectorial application to differential phase tomography.

PubMed

Mirone, Alessandro; Brun, Emmanuel; Coan, Paola

2014-01-01

X-ray based Phase-Contrast Imaging (PCI) techniques have been demonstrated to enhance the visualization of soft tissues in comparison to conventional imaging methods. Nevertheless the delivered dose as reported in the literature of biomedical PCI applications often equals or exceeds the limits prescribed in clinical diagnostics. The optimization of new computed tomography strategies which include the development and implementation of advanced image reconstruction procedures is thus a key aspect. In this scenario, we implemented a dictionary learning method with a new form of convex functional. This functional contains in addition to the usual sparsity inducing and fidelity terms, a new term which forces similarity between overlapping patches in the superimposed regions. The functional depends on two free regularization parameters: a coefficient multiplying the sparsity-inducing L1 norm of the patch basis functions coefficients, and a coefficient multiplying the L2 norm of the differences between patches in the overlapping regions. The solution is found by applying the iterative proximal gradient descent method with FISTA acceleration. The gradient is computed by calculating projection of the solution and its error backprojection at each iterative step. We study the quality of the solution, as a function of the regularization parameters and noise, on synthetic data for which the solution is a-priori known. We apply the method on experimental data in the case of Differential Phase Tomography. For this case we use an original approach which consists in using vectorial patches, each patch having two components: one per each gradient component. The resulting algorithm, implemented in the European Synchrotron Radiation Facility tomography reconstruction code PyHST, has proven to be efficient and well-adapted to strongly reduce the required dose and the number of projections in medical tomography.

Fast analytical scatter estimation using graphics processing units.

PubMed

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Min, Jonghwan; Pua, Rizza; Cho, Seungryong, E-mail: scho@kaist.ac.kr

Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in amore » circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the proposed scanning method and image reconstruction algorithm can effectively estimate the scatter in cone-beam projections and produce tomographic images of nearly scatter-free quality. The authors believe that the proposed method would provide a fast and efficient CBCT scanning option to various applications particularly including head-and-neck scan.« less

High resolution x-ray CMT: Reconstruction methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, J.K.

This paper qualitatively discusses the primary characteristics of methods for reconstructing tomographic images from a set of projections. These reconstruction methods can be categorized as either {open_quotes}analytic{close_quotes} or {open_quotes}iterative{close_quotes} techniques. Analytic algorithms are derived from the formal inversion of equations describing the imaging process, while iterative algorithms incorporate a model of the imaging process and provide a mechanism to iteratively improve image estimates. Analytic reconstruction algorithms are typically computationally more efficient than iterative methods; however, analytic algorithms are available for a relatively limited set of imaging geometries and situations. Thus, the framework of iterative reconstruction methods is better suited formore » high accuracy, tomographic reconstruction codes.« less

Data consistency criterion for selecting parameters for k-space-based reconstruction in parallel imaging.

PubMed

Nana, Roger; Hu, Xiaoping

2010-01-01

k-space-based reconstruction in parallel imaging depends on the reconstruction kernel setting, including its support. An optimal choice of the kernel depends on the calibration data, coil geometry and signal-to-noise ratio, as well as the criterion used. In this work, data consistency, imposed by the shift invariance requirement of the kernel, is introduced as a goodness measure of k-space-based reconstruction in parallel imaging and demonstrated. Data consistency error (DCE) is calculated as the sum of squared difference between the acquired signals and their estimates obtained based on the interpolation of the estimated missing data. A resemblance between DCE and the mean square error in the reconstructed image was found, demonstrating DCE's potential as a metric for comparing or choosing reconstructions. When used for selecting the kernel support for generalized autocalibrating partially parallel acquisition (GRAPPA) reconstruction and the set of frames for calibration as well as the kernel support in temporal GRAPPA reconstruction, DCE led to improved images over existing methods. Data consistency error is efficient to evaluate, robust for selecting reconstruction parameters and suitable for characterizing and optimizing k-space-based reconstruction in parallel imaging.

A review of GPU-based medical image reconstruction.

PubMed

Després, Philippe; Jia, Xun

2017-10-01

Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Method for position emission mammography image reconstruction

DOEpatents

Smith, Mark Frederick

2004-10-12

An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.

SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space

PubMed Central

Lustig, Michael; Pauly, John M.

2010-01-01

A new approach to autocalibrating, coil-by-coil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k-space sampling patterns. The formulation can flexibly incorporate additional image priors such as off-resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k-space domain are presented. These are based on a projection over convex sets (POCS) and a conjugate gradient (CG) algorithms. Phantom and in-vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off-resonance correction and nonlinear ℓ1-wavelet regularization are also demonstrated. PMID:20665790

Image Reconstruction is a New Frontier of Machine Learning.

PubMed

Wang, Ge; Ye, Jong Chu; Mueller, Klaus; Fessler, Jeffrey A

2018-06-01

Over past several years, machine learning, or more generally artificial intelligence, has generated overwhelming research interest and attracted unprecedented public attention. As tomographic imaging researchers, we share the excitement from our imaging perspective [item 1) in the Appendix], and organized this special issue dedicated to the theme of "Machine learning for image reconstruction." This special issue is a sister issue of the special issue published in May 2016 of this journal with the theme "Deep learning in medical imaging" [item 2) in the Appendix]. While the previous special issue targeted medical image processing/analysis, this special issue focuses on data-driven tomographic reconstruction. These two special issues are highly complementary, since image reconstruction and image analysis are two of the main pillars for medical imaging. Together we cover the whole workflow of medical imaging: from tomographic raw data/features to reconstructed images and then extracted diagnostic features/readings.

WE-AB-303-09: Rapid Projection Computations for On-Board Digital Tomosynthesis in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Pitsianis, N

2015-06-15

Purpose: To facilitate fast and accurate iterative volumetric image reconstruction from limited-angle on-board projections. Methods: Intrafraction motion hinders the clinical applicability of modern radiotherapy techniques, such as lung stereotactic body radiation therapy (SBRT). The LIVE system may impact clinical practice by recovering volumetric information via Digital Tomosynthesis (DTS), thus entailing low time and radiation dose for image acquisition during treatment. The DTS is estimated as a deformation of prior CT via iterative registration with on-board images; this shifts the challenge to the computational domain, owing largely to repeated projection computations across iterations. We address this issue by composing efficient digitalmore » projection operators from their constituent parts. This allows us to separate the static (projection geometry) and dynamic (volume/image data) parts of projection operations by means of pre-computations, enabling fast on-board processing, while also relaxing constraints on underlying numerical models (e.g. regridding interpolation kernels). Further decoupling the projectors into simpler ones ensures the incurred memory overhead remains low, within the capacity of a single GPU. These operators depend only on the treatment plan and may be reused across iterations and patients. The dynamic processing load is kept to a minimum and maps well to the GPU computational model. Results: We have integrated efficient, pre-computable modules for volumetric ray-casting and FDK-based back-projection with the LIVE processing pipeline. Our results show a 60x acceleration of the DTS computations, compared to the previous version, using a single GPU; presently, reconstruction is attained within a couple of minutes. The present implementation allows for significant flexibility in terms of the numerical and operational projection model; we are investigating the benefit of further optimizations and accurate digital projection sub-kernels. Conclusion: Composable projection operators constitute a versatile research tool which can greatly accelerate iterative registration algorithms and may be conducive to the clinical applicability of LIVE. National Institutes of Health Grant No. R01-CA184173; GPU donation by NVIDIA Corporation.« less

Investigation of iterative image reconstruction in low-dose breast CT

NASA Astrophysics Data System (ADS)

Bian, Junguo; Yang, Kai; Boone, John M.; Han, Xiao; Sidky, Emil Y.; Pan, Xiaochuan

2014-06-01

There is interest in developing computed tomography (CT) dedicated to breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence has been found that suggests that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image total-variation minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with a focus on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics.

Automatic correction of echo-planar imaging (EPI) ghosting artifacts in real-time interactive cardiac MRI using sensitivity encoding.

PubMed

Kim, Yoon-Chul; Nielsen, Jon-Fredrik; Nayak, Krishna S

2008-01-01

To develop a method that automatically corrects ghosting artifacts due to echo-misalignment in interleaved gradient-echo echo-planar imaging (EPI) in arbitrary oblique or double-oblique scan planes. An automatic ghosting correction technique was developed based on an alternating EPI acquisition and the phased-array ghost elimination (PAGE) reconstruction method. The direction of k-space traversal is alternated at every temporal frame, enabling lower temporal-resolution ghost-free coil sensitivity maps to be dynamically estimated. The proposed method was compared with conventional one-dimensional (1D) phase correction in axial, oblique, and double-oblique scan planes in phantom and cardiac in vivo studies. The proposed method was also used in conjunction with two-fold acceleration. The proposed method with nonaccelerated acquisition provided excellent suppression of ghosting artifacts in all scan planes, and was substantially more effective than conventional 1D phase correction in oblique and double-oblique scan planes. The feasibility of real-time reconstruction using the proposed technique was demonstrated in a scan protocol with 3.1-mm spatial and 60-msec temporal resolution. The proposed technique with nonaccelerated acquisition provides excellent ghost suppression in arbitrary scan orientations without a calibration scan, and can be useful for real-time interactive imaging, in which scan planes are frequently changed with arbitrary oblique orientations.

Bayesian image reconstruction - The pixon and optimal image modeling

NASA Technical Reports Server (NTRS)

Pina, R. K.; Puetter, R. C.

1993-01-01

In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

Hubble confirms cosmic acceleration with weak lensing

NASA Image and Video Library

2017-12-08

NASA/ESA Hubble Release Date: March 25, 2010 This image shows a smoothed reconstruction of the total (mostly dark) matter distribution in the COSMOS field, created from data taken by the NASA/ESA Hubble Space Telescope and ground-based telescopes. It was inferred from the weak gravitational lensing distortions that are imprinted onto the shapes of background galaxies. The colour coding indicates the distance of the foreground mass concentrations as gathered from the weak lensing effect. Structures shown in white, cyan, and green are typically closer to us than those indicated in orange and red. To improve the resolution of the map, data from galaxies both with and without redshift information were used. The new study presents the most comprehensive analysis of data from the COSMOS survey. The researchers have, for the first time ever, used Hubble and the natural "weak lenses" in space to characterise the accelerated expansion of the Universe. Credit: NASA, ESA, P. Simon (University of Bonn) and T. Schrabback (Leiden Observatory) To learn more abou this image go to: www.spacetelescope.org/news/html/heic1005.html For more information about Goddard Space Flight Center go here: www.nasa.gov/centers/goddard/home/index.html

Accelerating electron tomography reconstruction algorithm ICON with GPU.

PubMed

Chen, Yu; Wang, Zihao; Zhang, Jingrong; Li, Lun; Wan, Xiaohua; Sun, Fei; Zhang, Fa

2017-01-01

Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the "missing wedge" problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON's dependence on computing resource.

Influence of photon energy cuts on PET Monte Carlo simulation results.

PubMed

Mitev, Krasimir; Gerganov, Georgi; Kirov, Assen S; Schmidtlein, C Ross; Madzhunkov, Yordan; Kawrakow, Iwan

2012-07-01

The purpose of this work is to study the influence of photon energy cuts on the results of positron emission tomography (PET) Monte Carlo (MC) simulations. MC simulations of PET scans of a box phantom and the NEMA image quality phantom are performed for 32 photon energy cut values in the interval 0.3-350 keV using a well-validated numerical model of a PET scanner. The simulations are performed with two MC codes, egs_pet and GEANT4 Application for Tomographic Emission (GATE). The effect of photon energy cuts on the recorded number of singles, primary, scattered, random, and total coincidences as well as on the simulation time and noise-equivalent count rate is evaluated by comparing the results for higher cuts to those for 1 keV cut. To evaluate the effect of cuts on the quality of reconstructed images, MC generated sinograms of PET scans of the NEMA image quality phantom are reconstructed with iterative statistical reconstruction. The effects of photon cuts on the contrast recovery coefficients and on the comparison of images by means of commonly used similarity measures are studied. For the scanner investigated in this study, which uses bismuth germanate crystals, the transport of Bi X(K) rays must be simulated in order to obtain unbiased estimates for the number of singles, true, scattered, and random coincidences as well as for an unbiased estimate of the noise-equivalent count rate. Photon energy cuts higher than 170 keV lead to absorption of Compton scattered photons and strongly increase the number of recorded coincidences of all types and the noise-equivalent count rate. The effect of photon cuts on the reconstructed images and the similarity measures used for their comparison is statistically significant for very high cuts (e.g., 350 keV). The simulation time decreases slowly with the increase of the photon cut. The simulation of the transport of characteristic x rays plays an important role, if an accurate modeling of a PET scanner system is to be achieved. The simulation time decreases slowly with the increase of the cut which, combined with the accuracy loss at high cuts, means that the usage of high photon energy cuts is not recommended for the acceleration of MC simulations.

Anisotropic conductivity imaging with MREIT using equipotential projection algorithm.

PubMed

Değirmenci, Evren; Eyüboğlu, B Murat

2007-12-21

Magnetic resonance electrical impedance tomography (MREIT) combines magnetic flux or current density measurements obtained by magnetic resonance imaging (MRI) and surface potential measurements to reconstruct images of true conductivity with high spatial resolution. Most of the biological tissues have anisotropic conductivity; therefore, anisotropy should be taken into account in conductivity image reconstruction. Almost all of the MREIT reconstruction algorithms proposed to date assume isotropic conductivity distribution. In this study, a novel MREIT image reconstruction algorithm is proposed to image anisotropic conductivity. Relative anisotropic conductivity values are reconstructed iteratively, using only current density measurements without any potential measurement. In order to obtain true conductivity values, only either one potential or conductivity measurement is sufficient to determine a scaling factor. The proposed technique is evaluated on simulated data for isotropic and anisotropic conductivity distributions, with and without measurement noise. Simulation results show that the images of both anisotropic and isotropic conductivity distributions can be reconstructed successfully.

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, S; Zhang, Y; Ma, J

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinctmore » from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.« less

Evaluating the effect of increased pitch, iterative reconstruction and dual source CT on dose reduction and image quality.

PubMed

Gariani, Joanna; Martin, Steve P; Botsikas, Diomidis; Becker, Christoph D; Montet, Xavier

2018-06-14

To compare radiation dose and image quality of thoracoabdominal scans obtained with a high-pitch protocol (pitch 3.2) and iterative reconstruction (Sinogram Affirmed Iterative Reconstruction) in comparison to standard pitch reconstructed with filtered back projection (FBP) using dual source CT. 114 CT scans (Somatom Definition Flash, Siemens Healthineers, Erlangen, Germany), 39 thoracic scans, 54 thoracoabdominal scans and 21 abdominal scans were performed. Analysis of three protocols was undertaken; pitch of 1 reconstructed with FBP, pitch of 3.2 reconstructed with SAFIRE, pitch of 3.2 with stellar detectors reconstructed with SAFIRE. Objective and subjective image analysis were performed. Dose differences of the protocols used were compared. Dose was reduced when comparing scans with a pitch of 1 reconstructed with FBP to high-pitch scans with a pitch of 3.2 reconstructed with SAFIRE with a reduction of volume CT dose index of 75% for thoracic scans, 64% for thoracoabdominal scans and 67% for abdominal scans. There was a further reduction after the implementation of stellar detectors reflected in a reduction of 36% of the dose-length product for thoracic scans. This was not at the detriment of image quality, contrast-to-noise ratio, signal-to-noise ratio and the qualitative image analysis revealed a superior image quality in the high-pitch protocols. The combination of a high pitch protocol with iterative reconstruction allows significant dose reduction in routine chest and abdominal scans whilst maintaining or improving diagnostic image quality, with a further reduction in thoracic scans with stellar detectors. Advances in knowledge: High pitch imaging with iterative reconstruction is a tool that can be used to reduce dose without sacrificing image quality.