scholarly journals Effect of regularization parameter and scan time on crossing fibers with constrained compressed sensing

2011 ◽  
Author(s):  
Fatma Elzahraa A. ElShahaby ◽  
Bennett A. Landman ◽  
Jerry L. Prince
Keyword(s):  
Compressed Sensing ◽  
Regularization Parameter ◽  
Scan Time ◽  
Crossing Fibers

scholarly journals 3D Dixon water-fat LGE imaging with image navigator and compressed sensing in cardiac MRI

2020 ◽  
Author(s):  
Martin Georg Zeilinger ◽  
Marco Wiesmüller ◽  
Christoph Forman ◽  
Michaela Schmidt ◽  
Camila Munoz ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Compressed Sensing ◽  
Cardiac Mri ◽  
Three Dimensional ◽  
Fat Suppression ◽  
Diagnostic Confidence ◽  
Pericardial Disease ◽  
Scan Time ◽  
Wilcoxon Rank Sum Test

Abstract Objectives To evaluate an image-navigated isotropic high-resolution 3D late gadolinium enhancement (LGE) prototype sequence with compressed sensing and Dixon water-fat separation in a clinical routine setting. Material and methods Forty consecutive patients scheduled for cardiac MRI were enrolled prospectively and examined with 1.5 T MRI. Overall subjective image quality, LGE pattern and extent, diagnostic confidence for detection of LGE, and scan time were evaluated and compared to standard 2D LGE imaging. Robustness of Dixon fat suppression was evaluated for 3D Dixon LGE imaging. For statistical analysis, the non-parametric Wilcoxon rank sum test was performed. Results LGE was rated as ischemic in 9 patients and non-ischemic in 11 patients while it was absent in 20 patients. Image quality and diagnostic confidence were comparable between both techniques (p = 0.67 and p = 0.66, respectively). LGE extent with respect to segmental or transmural myocardial enhancement was identical between 2D and 3D (water-only and in-phase). LGE size was comparable (3D 8.4 ± 7.2 g, 2D 8.7 ± 7.3 g, p = 0.19). Good or excellent fat suppression was achieved in 93% of the 3D LGE datasets. In 6 patients with pericarditis, the 3D sequence with Dixon fat suppression allowed for a better detection of pericardial LGE. Scan duration was significantly longer for 3D imaging (2D median 9:32 min vs. 3D median 10:46 min, p = 0.001). Conclusion The 3D LGE sequence provides comparable LGE detection compared to 2D imaging and seems to be superior in evaluating the extent of pericardial involvement in patients suspected with pericarditis due to the robust Dixon fat suppression. Key Points • Three-dimensional LGE imaging provides high-resolution detection of myocardial scarring. • Robust Dixon water-fat separation aids in the assessment of pericardial disease. • The 2D image navigator technique enables 100% respiratory scan efficacy and permits predictable scan times.

An Adaptive Regularized Fast Iterative Shrinkage-Thresholding Algorithm for Image Reconstruction in Compressed Sensing

2013 ◽  
Vol 710 ◽  
pp. 593-597
Author(s):  
Xin Meng ◽  
Shi Fang Duan ◽  
She Xiang Ma
Keyword(s):  
Image Quality ◽  
Compressed Sensing ◽  
Objective Function ◽  
Time Complexity ◽  
Regularization Parameter ◽  
Iteration Process ◽  
Reconstructed Image ◽  
Iterative Shrinkage ◽  
Thresholding Algorithm ◽  
Iterative Shrinkage Thresholding

Aiming at the problems of worse reconstructed image quality and larger time complexity of the fast iterative shrinkage-thresholding algorithm in compressed sensing, this paper presents adaptive regularized fast iterative shrinkage-thresholding algorithm. This algorithm brings in the idea of adaptively selecting regularization parameter on the basis of using gradient method and threshold shrinkage to minimize the objective function. During the iteration process regularization parameter is adaptively selected from the whole value in order to adjust the proportion of the former part and the latter part of the objective function value. Simulation results show that the proposed algorithm, compared with the traditional algorithms, obtains the better reconstructed image quality and lower time complexity.

scholarly journals Radial Undersampling-Based Interpolation Scheme for Multislice CSMRI Reconstruction Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Maria Murad ◽  
Abdul Jalil ◽  
Muhammad Bilal ◽  
Shahid Ikram ◽  
Ahmad Ali ◽  
...  
Keyword(s):  
Image Quality ◽  
Compressed Sensing ◽  
Imaging Modality ◽  
Similarity Index ◽  
Structural Similarity ◽  
Maximum Information ◽  
Central Target ◽  
Radial Sampling ◽  
Scan Time ◽  
Index Measurement

Magnetic Resonance Imaging (MRI) is an important yet slow medical imaging modality. Compressed sensing (CS) theory has enabled to accelerate the MRI acquisition process using some nonlinear reconstruction techniques from even 10% of the Nyquist samples. In recent years, interpolated compressed sensing (iCS) has further reduced the scan time, as compared to CS, by exploiting the strong interslice correlation of multislice MRI. In this paper, an improved efficient interpolated compressed sensing (EiCS) technique is proposed using radial undersampling schemes. The proposed efficient interpolation technique uses three consecutive slices to estimate the missing samples of the central target slice from its two neighboring slices. Seven different evaluation metrics are used to analyze the performance of the proposed technique such as structural similarity index measurement (SSIM), feature similarity index measurement (FSIM), mean square error (MSE), peak signal to noise ratio (PSNR), correlation (CORR), sharpness index (SI), and perceptual image quality evaluator (PIQE) and compared with the latest interpolation techniques. The simulation results show that the proposed EiCS technique has improved image quality and performance using both golden angle and uniform angle radial sampling patterns, with an even lower sampling ratio and maximum information content and using a more practical sampling scheme.

scholarly journals Solar hard X-ray imaging by means of compressed sensing and finite isotropic wavelet transform

2018 ◽  
Vol 615 ◽  
pp. A59 ◽  
Author(s):  
M. A. Duval-Poo ◽  
M. Piana ◽  
A. M. Massone
Keyword(s):  
Wavelet Transform ◽  
Compressed Sensing ◽  
Regularization Parameter ◽  
Synthetic Data ◽  
High Energy ◽  
Morphological Properties ◽  
X Rays ◽  
X Ray ◽  
Reconstruction Methods ◽  
Thresholding Algorithm

Aims. Compressed sensing realized by means of regularized deconvolution and the finite isotropic wavelet transform is effective and reliable in hard X-ray solar imaging. Methods. The method uses the finite isotropic wavelet transform with the Meyer function as the mother wavelet. Furthermore, compressed sensing is realized by optimizing a sparsity-promoting regularized objective function by means of the fast iterative shrinkage-thresholding algorithm. Eventually, the regularization parameter is selected by means of the Miller criterion. Results. The method is applied against both synthetic data mimicking measurements made with the Spectrometer/Telescope Imaging X-rays (STIX) and experimental observations provided by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). The performances of the method are qualitatively validated by comparing some morphological properties of the reconstructed sources with those of the corresponding synthetic configurations. Furthermore, the results concerning experimental data are compared with those obtained by applying other visibility-based reconstruction methods. Conclusions. The results show that when the new method is applied to synthetic STIX visibility sets, it provides reconstructions with a spatial accuracy comparable to the accuracy provided by the most popular method in hard X-ray solar imaging and with a higher spatial resolution. Furthermore, when it is applied to experimental RHESSI data, the reconstructions are characterized by reliable photometry and by a notable reduction of the ringing effects caused by the instrument point spread function.

scholarly journals Highly Accelerated Vessel-Selective Arterial Spin Labelling Angiography using Sparsity and Smoothness Constraints

2019 ◽  
Author(s):  
Sophie Schauman ◽  
Mark Chiew ◽  
Thomas W. Okell
Keyword(s):  
Image Quality ◽  
Compressed Sensing ◽  
Arterial Spin Labeling ◽  
Parallel Imaging ◽  
Spin Labeling ◽  
Dominant Factor ◽  
Image Domain ◽  
In Vivo Experiments ◽  
Scan Time

AbstractPurposeTo demonstrate that vessel-selectivity in arterial spin labeling angiography can be achieved without any scan time penalty or noticeable loss of image quality compared to conventional arterial spin labeling angiography.MethodsSimulations on a numerical phantom were used to assess whether the increased sparsity of vessel-encoded angiograms compared to non-vessel-encoded angiograms alone can improve reconstruction results in a compressed sensing framework. Further simulations were performed to study whether the difference in relative sparsity between non-selective and vessel-selective dynamic angiograms were sufficient to achieve similar image quality at matched scan times in the presence of noise. Finally, data were acquired from 5 healthy volunteers to validate the technique in vivo. All data, both simulated and in vivo, were sampled in 2D using a golden angle radial trajectory and reconstructed by enforcing both image domain sparsity and temporal smoothness on the angiograms in a parallel imaging and compressed sensing framework.ResultsRelative sparsity was established as a primary factor governing the reconstruction fidelity. Using the proposed reconstruction scheme, differences between vessel-selective and non-selective angiography were negligible compared to the dominant factor of total scan time in both simulations and in vivo experiments at acceleration factors up to R = 34. The reconstruction quality was not heavily dependent on hand-tuning the parameters of the reconstruction.ConclusionThe increase in relative sparsity of vessel-selective angiograms compared to non-selective angiograms can be leveraged to achieve higher acceleration without loss of image quality, resulting in the acquisition of vessel-selective information at no scan time cost.

scholarly journals Resolution of crossing fibers with constrained compressed sensing using traditional diffusion tensor MRI

2010 ◽  
Author(s):  
Bennett A. Landman ◽  
Hanlin Wan ◽  
John A. Bogovic ◽  
Pierre-Louis Bazin ◽  
Jerry L. Prince
Keyword(s):  
Compressed Sensing ◽  
Diffusion Tensor ◽  
Diffusion Tensor Mri ◽  
Crossing Fibers

scholarly journals Rapid cardiovascular magnetic resonance protocol utilizing compressed sensing real-time imaging during the COVID-19 pandemic

2021 ◽  
Vol 22 (Supplement_2) ◽  
Author(s):  
K Gil ◽  
KM Zareba ◽  
S Rajpal ◽  
OP Simonetti ◽  
D Addison ◽  
...  
Keyword(s):  
Cardiovascular Magnetic Resonance ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Real Time ◽  
Process Improvement ◽  
Temporal Resolution ◽  
Standard Protocol ◽  
Relative Time ◽  
Scan Time ◽  
Time Reduction

Abstract Funding Acknowledgements Type of funding sources: None. Background Coronavirus Disease 2019 (COVID-19) poses many workflow challenges for healthcare systems. Elective cardiovascular magnetic resonance (CMR) exams were postponed until safety protocols were instituted. Since reopening, imaging labs are managing COVID-19 safety triaging, exam backlog, and increased referrals, thus innovative solutions for process improvement are needed. Purpose An accelerated compressed sensing (CS) real-time (RT) technique offers dynamic cardiac imaging with high spatial and temporal resolution without image degradation. We sought to evaluate the efficiency of a rapid RT CMR protocol with a goal to decrease scan time without compromising study quality and comprehensiveness. Methods We retrospectively evaluated 219 CMRs (Siemens Magnetom Sola 1.5T) performed 09/01/2020 - 10/15/2020. After excluding 81 exams due to heterogeneous protocols (Figure 1), we analyzed 138 CMR exams using standard cardiomyopathy or myocarditis protocols. CMR studies utilized either a rapid RT short axis (SAX) cine (spatial resolution of 2.5 mm2 or better and temporal resolution of 55 ms or better) or standard breath-held (BH) SAX cine protocol (Figure 2).  Protocols were chosen by the interpreting physician. Previous internal quality control demonstrated similar volumetric quantification between RT and BH SAX cines. RT cines were reconstructed inline using a CS-based method.  We analyzed the length of time needed to complete each protocol and the number of series performed. Statistical analysis included student t-test with p value <0.05 considered significant. Results Of 138 analyzed CMR exams, there were 23 rapid protocols and 115 standard protocols performed. The mean image acquisition time for the rapid protocol was significantly shorter at 26 ± 6 minutes (range 18-44 min) vs 33 ± 6 minutes (range 22-49 min) for the standard protocol, p < 0.001. This represents a mean relative reduction in scan time of 21%. More time was saved in rapid myocarditis (scan time 25 ± 6 min vs 34 ± 6 min, p = 0.01; relative time reduction 26%) vs rapid cardiomyopathy protocols (scan time 27 ± 6 min vs 31 ± 6 min, p = 0.04; relative time reduction 13%). There was no significant difference in the number of series performed (62 ± 14 series in rapid vs 67 ± 11 series in standard protocols, p = 0.09).  T1 and T2 maps constituted the same percentage of acquired images regardless of protocol used (T1 maps 1.8% vs 1.7% for cardiomyopathy, 1.4% vs 1.4% for myocarditis in standard vs rapid protocols respectively; T2 maps 1.8% vs 1.7% for cardiomyopathy, 5.6% vs 5.8% for myocarditis in standard vs rapid protocols respectively). Conclusions A rapid CMR protocol utilizing a CS-based RT imaging is significantly shorter as compared to the standard protocol with adequate diagnostic quality. Rapid CMR protocols are an effective tool for process improvement during the COVID-19 pandemic.

scholarly journals Accelerated aortic 4D flow cardiovascular magnetic resonance using compressed sensing: applicability, validation and clinical integration

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Elisabeth Neuhaus ◽  
Kilian Weiss ◽  
Rene Bastkowski ◽  
Jonas Koopmann ◽  
David Maintz ◽  
...  
Keyword(s):  
Cardiovascular Magnetic Resonance ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Thoracic Aorta ◽  
4D Flow ◽  
Particle Trace ◽  
4D Flow Cmr ◽  
Scan Time ◽  
On Line ◽  
Mean Differences

Abstract Background Three-dimensional time-resolved phase-contrast cardiovascular magnetic resonance (4D flow CMR) enables the quantification and visualisation of blood flow, but its clinical applicability remains hampered by its long scan time. The aim of this study was to evaluate the use of compressed sensing (CS) with on-line reconstruction to accelerate the acquisition and reconstruction of 4D flow CMR of the thoracic aorta. Methods 4D flow CMR of the thoracic aorta was acquired in 20 healthy subjects using CS with acceleration factors ranging from 4 to 10. As a reference, conventional parallel imaging (SENSE) with acceleration factor 2 was used. Flow curves, net flows, peak flows and peak velocities were extracted from six contours along the aorta. To measure internal data consistency, a quantitative particle trace analysis was performed. Additionally, scan-rescan, inter- and intraobserver reproducibility were assessed. Subsequently, 4D flow CMR with CS factor 6 was acquired in 3 patients with differing aortopathies. The flow patterns resulting from particle trace visualisation were qualitatively analysed. Results All collected data were successfully acquired and reconstructed on-line. The average acquisition time including respiratory navigator efficiency with CS factor 6 was 5:02 ± 2:23 min while reconstruction took approximately 9 min. For CS factors of 8 or less, mean differences in net flow, peak flow and peak velocity as compared to SENSE were below 2.2 ± 7.8 ml/cycle, 4.6 ± 25.2 ml/s and − 7.9 ± 13.0 cm/s, respectively. For a CS factor of 10 differences reached 5.4 ± 8.0 ml/cycle, 14.4 ± 28.3 ml/s and − 4.0 ± 12.2 cm/s. Scan-rescan analysis yielded mean differences in net flow of − 0.7 ± 4.9 ml/cycle for SENSE and − 0.2 ± 8.5 ml/cycle for CS factor of 6. Conclusions A six- to eightfold acceleration of 4D flow CMR using CS is feasible. Up to a CS acceleration rate of 6, no statistically significant differences in measured flow parameters could be observed with respect to the reference technique. Acquisitions in patients with aortopathies confirm the potential to integrate the proposed method in a clinical routine setting, whereby its main benefits are scan-time savings and direct on-line reconstruction.

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