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Статті в журналах з теми "Spiral k space sampling":
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Katoh, Marcus, Elmar Spuentrup, Arno Buecker, Warren J. Manning, Rolf W. Günther, and Rene M. Botnar. "MR coronary vessel wall imaging: Comparison between radial and spiral k-space sampling." Journal of Magnetic Resonance Imaging 23, no. 5 (May 2006): 757–62. http://dx.doi.org/10.1002/jmri.20569.
Speidel, T., P. Metze, and V. Rasche. "Efficient 3D Low-Discrepancy ${k}$ -Space Sampling Using Highly Adaptable Seiffert Spirals." IEEE Transactions on Medical Imaging 38, no. 8 (August 2019): 1833–40. http://dx.doi.org/10.1109/tmi.2018.2888695.
Lorch, Benedikt, Ghislain Vaillant, Christian Baumgartner, Wenjia Bai, Daniel Rueckert, and Andreas Maier. "Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests." Journal of Medical Engineering 2017 (June 11, 2017): 1–9. http://dx.doi.org/10.1155/2017/4501647.
The acquisition of a Magnetic Resonance (MR) scan usually takes longer than subjects can remain still. Movement of the subject such as bulk patient motion or respiratory motion degrades the image quality and its diagnostic value by producing image artefacts like ghosting, blurring, and smearing. This work focuses on the effect of motion on the reconstructed slices and the detection of motion artefacts in the reconstruction by using a supervised learning approach based on random decision forests. Both the effects of bulk patient motion occurring at various time points in the acquisition on head scans and the effects of respiratory motion on cardiac scans are studied. Evaluation is performed on synthetic images where motion artefacts have been introduced by altering the k-space data according to a motion trajectory, using the three common k-space sampling patterns: Cartesian, radial, and spiral. The results suggest that a machine learning approach is well capable of learning the characteristics of motion artefacts and subsequently detecting motion artefacts with a confidence that depends on the sampling pattern.
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Martin, Joe, Matthieu Ruthven, Redha Boubertakh, and Marc E. Miquel. "Realistic Dynamic Numerical Phantom for MRI of the Upper Vocal Tract." Journal of Imaging 6, no. 9 (August 27, 2020): 86. http://dx.doi.org/10.3390/jimaging6090086.
Dynamic and real-time MRI (rtMRI) of human speech is an active field of research, with interest from both the linguistics and clinical communities. At present, different research groups are investigating a range of rtMRI acquisition and reconstruction approaches to visualise the speech organs. Similar to other moving organs, it is difficult to create a physical phantom of the speech organs to optimise these approaches; therefore, the optimisation requires extensive scanner access and imaging of volunteers. As previously demonstrated in cardiac imaging, realistic numerical phantoms can be useful tools for optimising rtMRI approaches and reduce reliance on scanner access and imaging volunteers. However, currently, no such speech rtMRI phantom exists. In this work, a numerical phantom for optimising speech rtMRI approaches was developed and tested on different reconstruction schemes. The novel phantom comprised a dynamic image series and corresponding k-space data of a single mid-sagittal slice with a temporal resolution of 30 frames per second (fps). The phantom was developed based on images of a volunteer acquired at a frame rate of 10 fps. The creation of the numerical phantom involved the following steps: image acquisition, image enhancement, segmentation, mask optimisation, through-time and spatial interpolation and finally the derived k-space phantom. The phantom was used to: (1) test different k-space sampling schemes (Cartesian, radial and spiral); (2) create lower frame rate acquisitions by simulating segmented k-space acquisitions; (3) simulate parallel imaging reconstructions (SENSE and GRAPPA). This demonstrated how such a numerical phantom could be used to optimise images and test multiple sampling strategies without extensive scanner access.
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Swami, Vimarsha G., Mihir Katlariwala, Sukhvinder Dhillon, Zaid Jibri, and Jacob L. Jaremko. "Magnetic Resonance Imaging in Patients with Mechanical Low Back Pain Using a Novel Rapid-Acquisition Three-Dimensional SPACE Sequence at 1.5-T: A Pilot Study Comparing Lumbar Stenosis Assessment with Routine Two-Dimensional Magnetic Resonance Sequences." Canadian Association of Radiologists Journal 67, no. 4 (November 2016): 368–78. http://dx.doi.org/10.1016/j.carj.2015.11.005.
Purpose To minimize the burden of overutilisation of lumbar spine magnetic resonance imaging (MRI) on a resource-constrained public healthcare system, it may be helpful to image some patients with mechanical low-back pain (LBP) using a simplified rapid MRI screening protocol at 1.5-T. A rapid-acquisition 3-dimensional (3D) SPACE (Sampling Perfection with Application-optimized Contrasts using different flip angle Evolution) sequence can demonstrate common etiologies of LBP. We compared lumbar spinal canal stenosis (LSCS) and neural foraminal stenosis (LNFS) assessment on 3D SPACE against conventional 2-dimensional (2D) MRI. Methods We prospectively performed 3D SPACE and 2D spin-echo MRI sequences (axial or sagittal T1-weighted or T2-weighted) at 1.5-T in 20 patients. Two blinded readers assessed levels L3-4, L4-5 and L5-S1 using: 1) morphologic grading systems, 2) global impression on the presence or absence of clinically significant stenosis (n = 60 disc levels for LSCS, n = 120 foramina for LNFS). Reliability statistics were calculated. Results Acquisition time was ∼5 minutes for SPACE and ∼20 minutes for 2D MRI sequences. Interobserver agreement of LSCS was substantial to near perfect on both sequences (morphologic grading: kappa [k] = 0.71 SPACE, k = 0.69 T2-weighted; global impression: k = 0.85 SPACE, k = 0.78 T2-weighted). LNFS assessment had superior interobserver reliability using SPACE than T1-weighted (k = 0.54 vs 0.37). Intersequence agreement of findings between SPACE and 2D MRI was substantial to near perfect by global impression (LSCS: k = 0.78 Reader 1, k = 0.85 Reader 2; LNFS: k = 0.63 Reader 1, k = 0.66 Reader 2). Conclusions 3D SPACE was acquired in one-quarter the time as the conventional 2D MRI protocol, had excellent agreement with 2D MRI for stenosis assessment, and had interobserver reliability superior to 2D MRI. These results justify future work to explore the role of 3D SPACE in a rapid MRI screening protocol at 1.5-T for mechanical LBP.
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Glover, Gary H. "Simple analytic spiral K-space algorithm." Magnetic Resonance in Medicine 42, no. 2 (August 1999): 412–15. http://dx.doi.org/10.1002/(sici)1522-2594(199908)42:2<412::aid-mrm25>3.0.co;2-u.
Tan, Hao, and Craig H. Meyer. "Estimation of k -space trajectories in spiral MRI." Magnetic Resonance in Medicine 61, no. 6 (April 7, 2009): 1396–404. http://dx.doi.org/10.1002/mrm.21813.
Noll, Douglas C. "Methodologic considerations for spiral k-space functional MRI." International Journal of Imaging Systems and Technology 6, no. 2-3 (1995): 175–83. http://dx.doi.org/10.1002/ima.1850060207.
Noll, Douglas C., Jonathan D. Cohen, Craig H. Meyer, and Walter Schneider. "Spiral K-space MR imaging of cortical activation." Journal of Magnetic Resonance Imaging 5, no. 1 (January 1995): 49–56. http://dx.doi.org/10.1002/jmri.1880050112.
Claeser, Robert Verfasser], Achim [Akademischer Betreuer] Stahl, N. Jon [Akademischer Betreuer] [Shah, and Dorit [Akademischer Betreuer] Merhof. "Fast mapping of the T1-relaxation in magnetic resonance imaging with advanced spiral k-space sampling and interleaving methods at 3 Tesla and 7 Tesla / Robert Claeser ; Achim Stahl, N. Jon Shah, Dorit Merhof." Aachen : Universitätsbibliothek der RWTH Aachen, 2021. http://d-nb.info/1240480318/34.
L’imagerie spectroscopique (IS) par résonance magnétique nucléaire du cerveau permet d’identifier les biomarqueurs du métabolisme cérébral sain ou pathologique. À court TE, les métabolites ayant des couplages J forts et des temps de relaxation T2 courts peuvent être détectées. Le rapport signal sur bruit et la résolution spectrale croît avec l’intensité du champ B0. Cependant, l’hétérogénéité des champs B0 et B1 ainsi que les erreurs associées au déplacement chimique augmentent avec B0. De bons profils de sélection sont obtenus avec le module de sélection du volume d’intérêt de type semi-LASER comparés à ceux obtenus avec des impulsions conventionnelles. De plus, cette séquence est moins sensible aux hétérogénéités du champ B1 et les erreurs liées au déplacement chimique sont moins importantes. La limitation la plus contraignante de la technique d’imagerie spectroscopique conventionnelle est probablement sa longue durée d’acquisition qui dépend de la résolution spatiale. L’imagerie spectroscopique spatiale (ISS) en encodant simultanément l’information spatiale et spectrale réduit considérablement le temps d’acquisition minimum. Il devient ainsi possible d’acquérir des données supplémentaires telles qu’une dimension spatiale et/ou une deuxième dimension spectrale. Nous avons mis en place une technique d’imagerie spectroscopique spirale pour l’étude du cerveau humain. Le TE est de 17 ms dans le cas de sélection du volume d’intérêt avec le module PRESS utilisant des impulsions RF conventionnelles et de 32 ms dans le cas de semi-LASER. Ces modules de sélection ont été combinés avec des modules de saturation des signaux de l’eau et du volume externe adaptés. Nous avons développé les programmes de calcul de la trajectoire mesurée et de la reconstruction des données à deux dimensions spatiales et une dimension spectrale. Nous avons obtenu une bonne saturation des lipides extra crâniens. Nous avons obtenu de meilleurs profils et une nette réduction des erreurs associées au déplacement chimique avec le module semi-LASER comparé avec ceux obtenus avec le module PRESS. L’application de la trajectoire mesurée à la reconstruction des données réduit les artefacts associés aux imperfections du système de gradients. Sur les spectres acquis à un TE de 17 ms (PRESS) et de 32 ms (semi-LASER) nous avons quantifié significativement le NAA, la choline, la créatine et le myo-inositol. Nous avons démontré la faisabilité de l’acquisition de données d’imagerie spectroscopique spirale volumétrique à TE court chez l’homme à 3T en une durée compatible avec celle des examens cliniques. D’autres travaux doivent être réalisés afin d’optimiser la séquence semi-LASER pour la détection de métabolites fortement couplés, comme le glutamate et la glutamine Proton magnetic resonance chemical shift imaging (CSI) at short time (TE) in vivo allows characterization of the spatial distribution of strongly J-coupled and short T2 biomarkers relevant to healthy or pathologic metabolism. We have developed a volumetric CSI technique for human brain studies at 3 Tesla in an experiment time compatible with patient examination. Pulse sequence modules for selection of the volume of interest (PRESS and semi-LASER), and for suppression of water and outer volume signals were implemented and optimized. The use of spiral K-space trajectories allowed acquisition speed-up by simultaneous encoding of spatial and spectral dimensions. Techniques of calibration and optimisation of the effective trajectory were developed, as well as an algorithm for reconstruction of 2 or 3 D spatial – 1 D spectral data sets. The method was validated in vivo on human brain with TEs of 17 ms (PRESS) or 32 ms (semi-LASER), on healthy subjects. Good saturation of subcutaneous lipids was obtained. Semi-LASER, by its use of adiabatic RF pulses, brought both sharper spatial selection profiles less sensitive to B1 inhomogeneity, and reduced chemical shift displacement errors. Using the measured trajectory for data reconstruction reduced artefacts associated with gradient hardware imperfections. NAA, Creatine, Choline, myo-Inositol and Glutamate/Glutamine were significantly quantified both with PRESS and semi-LASER. Clinical application of short TE volumetric spiral CSI at 3T can be considered
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Parasoglou, Prodromos, Andrew J. Sederman, John Rasburn, Hugh Powell, and Michael L. Johns. "Optimal k-space sampling for single point imaging of transient systems." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-192138.
A modification of the Single Point Imaging (SPI) is presented. The novel approach aims at increasing the sensitivity of the method and hence the resulting Signal-to-Noise ratio (SNR) for a given total time interval. With prior knowledge of the shape of the object
under study, a selective sparse k-space sampling can then be used to follow dynamic phenomena of transient systems, in this case the absorption of moisture by a cereal-based wafer material. Further improvement in the image quality is achieved when the un-sampled k-space points are replaced by those of the initial dry or the final wet sample acquired at the beginning and the end of the acquisition respectively when there are no acquisition time limitations.
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Parasoglou, Prodromos, Andrew J. Sederman, John Rasburn, Hugh Powell, and Michael L. Johns. "Optimal k-space sampling for single point imaging of transient systems." Diffusion fundamentals 10 (2009) 13, S. 1-3, 2009. https://ul.qucosa.de/id/qucosa%3A14104.
A modification of the Single Point Imaging (SPI) is presented. The novel approach aims at increasing the sensitivity of the method and hence the resulting Signal-to-Noise ratio (SNR) for a given total time interval. With prior knowledge of the shape of the object
under study, a selective sparse k-space sampling can then be used to follow dynamic phenomena of transient systems, in this case the absorption of moisture by a cereal-based wafer material. Further improvement in the image quality is achieved when the un-sampled k-space points are replaced by those of the initial dry or the final wet sample acquired at the beginning and the end of the acquisition respectively when there are no acquisition time limitations.
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Speidel, Tobias [Verfasser]. "Low-discrepancy k-space sampling strategies for magnetic resonance imaging / Tobias Speidel." Ulm : Universität Ulm, 2021. http://d-nb.info/1232323853/34.
In this master thesis methods for increasing temporal resolution when reconstructing radially sampled MRI data have been developed and evaluated. This has been done in two steps; first the order in which data is sampled in k-space has been optimized, and second; temporal filters have been developed in order to utilize the high sampling density in central regions of k-space as a result of the polar sampling geometry to increase temporal resolution while maintaining image quality.By properly designing the temporal filters the temporal resolution is increased by a factor 3–20 depending on other variables such as imageresolution and the size of the time varying areas in the image. The results are obtained from simulated raw data and subsequent reconstruction. The next step should be to acquire and reconstruct raw data to confirm the results. This Master thesis work was performed at Dept. Radiation Physis, Linköping University, but examined at Dept. Radiation Physics, Umeå University
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Lauzon, M. Louis. "The effects of sampling, reconstruction, and T(2) modulation for polar k-space acquistions in magnetic resonance imaging." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ31087.pdf.
Ullvin, Amanda. "Reduction of streak artifacts in radial MRI using CycleGAN." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284344.
One way of reducing the examination time in magnetic resonance imaging (MRI) is to reduce the amount of raw data acquired, by performing so-called undersampling. Conventionally, MRI data is acquired line-by-line on a Cartesian grid. In the field of Cardiovascular Magnetic Resonance (CMR), however, radial k-space sampling is seen as a promising emerging technique for rapid image acquisitions, mainly due to its robustness against motion disturbances occurring from the beating heart. Whereas Cartesian undersampling will result in image aliasing, radial undersampling will introduce streak artifacts. The objective of this work was to train the deep learning architecture, CycleGAN, to reduce streak artifacts in radially undersampled CMR images, and to evaluate the model performance. A benefit of using CycleGAN over other deep learning techniques for this application is that it can be trained on unpaired data. In this work, CycleGAN network was trained on 3060 radial and 2775 Cartesian unpaired CMR images acquired in human subjects to learn a mapping between the two image domains. The model was evaluated in comparison to images reconstructed using another emerging technique called GRASP. Whereas more investigation is warranted, the results are promising, suggesting that CycleGAN could be a viable method for effective streak-reduction in clinical applications.
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"Fast, Variable System Delay Correction for Spiral MRI." Master's thesis, 2013. http://hdl.handle.net/2286/R.I.20830.
abstract: Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality. Dissertation/Thesis M.S. Bioengineering 2013
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Chiu, Su-Chin, and 邱書瑾. "Gradient-echo EPI distortions correction using a over-sampling low-ky pulse sequence and k-space energy spectrum analysis." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/60393622736982390297.
碩士 國立臺灣大學 電機工程學研究所 95 The geometric distortion in echo-planar imaging (EPI) and its correction are systematically investigated in this thesis. EPI is one of the fastest MRI acquisition pulse sequence and is widely used for dynamic studies. However, in the presence of the field inhomogeneities, the EPI k-space energy peaks are displaced, which result in geometric distortions in the reconstructed images. Here we use the k-space energy spectrum analysis to calculate the k-space energy displacement in EPI. The calculated k-space energy displacement map can be converted to the field inhomogeneity map, which can then be applied to correct the EPI distortions using a phase modulation post-processing procedure. The EPI data corrected with the previously developed k-space energy spectrum based method, however, may have residual distortions due to an unknown B0 reference and the accumulated errors during the integration procedure. To further improve the accuracy and reliability of EPI distortion correction, we propose to combine the k-space energy spectrum analysis and an altered EPI acquisition strategy, in which the central part of the k-space is double sampled. In this approach, the B0 reference can be obtained from the embedded low-resolution double-TE data. In addition, the error accumulation in the integration procedure can be minimized.
Experimental results show that the new method can effectively remove EPI geometric distortions.
Книги з теми "Spiral k space sampling":
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Wolbarst, Anthony, and Nathan Yanasak. An Introduction to MRI. Medical Physics Publishing, 2019. http://dx.doi.org/10.54947/9781930524200.
This introduction to the science and technology of MRI has been written at the beginning graduate level primarily for professional medical physicists and engineers in training. Others, such as physicians with physical science backgrounds, may well also find it to be of interest. From Devon Godfrey in Medical Physics International… "The authors manage to successfully take the reader on a journey from the discovery and fundamentals of NMR all the way to novel k-space sampling and advanced MR imaging sequences—and their underlying molecular physics—in a manner that is quite thorough, yet should be approachable even to a reader with limited prior MRI knowledge. I believe this will be an excellent source for graduate students and professionals alike, and intend to incorporate it into my own teaching." From Andrew Maidment in Medical Physics…"As with all of Wolbarst’s books, the figures are of high quality, and I am sure they will find their way into many PowerPoint presentations in the future." This book will help readers understand not just the basics of MRI, but how recent variations on its original implementation have produced the many alternative interpretations of data that have made MRI such a powerful diagnostic tool. Several more advanced topics—like Fourier analysis, k-space, and statistical distributions—are introduced as they are needed.
Частини книг з теми "Spiral k space sampling":
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Wajer, F. T. A. W., G. H. L. A. Stijnman, M. Bourgeois, D. Graveron-Demilly, and D. van Ormondt. "Magnetic Resonance Image Reconstruction from Nonuniformly Sampled k-space Data." In Nonuniform Sampling, 439–78. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1229-5_10.
Bremer, Jörg, Johannes Gerster, Birk Brückner, Marcel Sarstedt, Sebastian Lehnhoff, and Lutz Hofmann. "Agent-Based Phase Space Sampling of Ensembles Using Ripley’s K for Homogeneity." In Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection, 191–202. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85710-3_16.
Zhang, Jinwei, Hang Zhang, Alan Wang, Qihao Zhang, Mert Sabuncu, Pascal Spincemaille, Thanh D. Nguyen, and Yi Wang. "Extending LOUPE for K-Space Under-Sampling Pattern Optimization in Multi-coil MRI." In Machine Learning for Medical Image Reconstruction, 91–101. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61598-7_9.
BERNSTEIN, MATT A., KEVIN F. KING, and XIAOHONG JOE ZHOU. "SIGNAL ACQUISITION AND K-SPACE SAMPLING." In Handbook of MRI Pulse Sequences, 367–442. Elsevier, 2004. http://dx.doi.org/10.1016/b978-012092861-3/50017-0.
BERNSTEIN, MATT A., KEVIN F. KING, and XIAOHONG JOE ZHOU. "INTRODUCTION TO DATA ACQUISITION, K-SPACE SAMPLING, AND IMAGE RECONSTRUCTION." In Handbook of MRI Pulse Sequences, 363–66. Elsevier, 2004. http://dx.doi.org/10.1016/b978-012092861-3/50016-9.
Kozerke, Sebastian, Redha Boubertakh, and Marc Miquel. "Scan acceleration." In The EACVI Textbook of Cardiovascular Magnetic Resonance, edited by Massimo Lombardi, Sven Plein, Steffen Petersen, Chiara Bucciarelli-Ducci, Emanuela R. Valsangiacomo Buechel, Cristina Basso, and Victor Ferrari, 14–16. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198779735.003.0004.
In cardiovascular magnetic resonance imaging, scan time is of critical importance, as many applications require breath-holding to suppress respiratory-related image artefacts. In this chapter, approaches to reduce scan time, while maintaining resolution, are described. Besides partial sampling of k-space, non-Cartesian k-space trajectories are introduced, followed by an overview of data under-sampling techniques as they are implemented on clinical magnetic resonance systems. Advantages and limitations of each of these methods are briefly described.
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Kozerke, Sebastian, Redha Boubertakh, and Marc Miquel. "Spatial encoding and image reconstruction." In The EACVI Textbook of Cardiovascular Magnetic Resonance, edited by Massimo Lombardi, Sven Plein, Steffen Petersen, Chiara Bucciarelli-Ducci, Emanuela R. Valsangiacomo Buechel, Cristina Basso, and Victor Ferrari, 11–13. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198779735.003.0003.
In order to form images with the required resolution and anatomical coverage, gradient magnetic fields are used to excite magnetization in a predefined slice or slab, with subsequent spatial encoding to obtain spatial resolution in the slice or slab. It is demonstrated how the spatial encoding principle is implemented and how it can be conceptualized using the so-called k-space representation. The relations between the field of view, spatial resolution, and k-space sampling are illustrated, along with the implementation using a simple pulse sequence. Once magnetic resonance data have been collected in k-space, the process of image reconstruction will yield the final images.
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"Exploratory Data Analysis." In Spatial Analysis Techniques Using MyGeoffice®, 112–36. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3270-5.ch006.
Тези доповідей конференцій з теми "Spiral k space sampling":
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Vellagoundar, Jaganathan, and M. Ramasubba Reddy. "Optimal k-space sampling scheme for compressive sampling MRI." In 2012 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES 2012). IEEE, 2012. http://dx.doi.org/10.1109/iecbes.2012.6498108.
Kim, Kyuyeol, Richard Wu, and Seha Choi. "K-space sampling using various filters and fourier image reconstruction." In 2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). IEEE, 2014. http://dx.doi.org/10.1109/spmb.2014.7002954.
Naidu, Kiranmai, and Luke Lin. "Data Dome: full k-space sampling data for high-frequency radar research." In Defense and Security, edited by Edmund G. Zelnio and Frederick D. Garber. SPIE, 2004. http://dx.doi.org/10.1117/12.548773.
Tolouee, Azar, Javad Alirezaie, and Paul Babyn. "Accelerating dynamic MRI by compressed sensing reconstruction from undersampled k-t space with spiral trajectories." In 2014 Middle East Conference on Biomedical Engineering (MECBME). IEEE, 2014. http://dx.doi.org/10.1109/mecbme.2014.6783197.
Oliaiee, Ashkan, Aboozar Ghaffari, and Emad Fatemizadeh. "MRI image reconstruction via new K-space sampling scheme based on separable transform." In 2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP). IEEE, 2013. http://dx.doi.org/10.1109/iranianmvip.2013.6779963.
Riederer, Stephen J., Casey P. Johnson, and Petrice M. Mostardi. "The use of Cartesian k-space sampling techniques for high quality 3D time-resolved imaging of the cardiovascular system." In 2010 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010). IEEE, 2010. http://dx.doi.org/10.1109/itab.2010.5687805.
Hershey, Bradley L., Rohan A. More, Mark Doyle, Eduardo Kortright, and Andreas S. Anayiotos. "Fast MRI Flow Imaging by Sparse Sampling and Segmentation." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59446.
Clinical use of cardiac synchronized Magnetic Resonance Imaging has been limited because of long unacceptable acquisition times. BRISK (Block Regional Interpolation Scheme for k-space) is a rapid MRI technique, which employs temporal sparse sampling scheme that varies the sampling rate as a function of distance from the k-space center. Using combination of conventional segmentation and BRISK approach, a new rapid phase contrast cine approach named FAST was investigated. FAST technique samples contiguous regions of k-space using a segmentation factor, just as in conventional segmentation, with the difference that the segmentation factor (SF) is varied as a function of distance from the k-space center. FAST and BRISK can be performed in nearly equally scan times. Both retained excellent axial-velocity accuracy. However secondary velocities, which were two orders of magnitude lower than the primary, suffered from comparable inaccuracies and distortion in conventional segmentation, BRISK and FAST.
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Mohan, Mahesh, and Claire Monteleoni. "Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/347.
In this paper we present a framework for spectral clustering based on the following simple scheme: sample a subset of the input points, compute the clusters for the sampled subset using weighted kernel k-means (Dhillon et al. 2004) and use the resulting centers to compute a clustering for the remaining data points. For the case where the points are sampled uniformly at random without replacement, we show that the number of samples required depends mainly on the number of clusters and the diameter of the set of points in the kernel space. Experiments show that the proposed framework outperforms the approaches based on the Nystrom approximation both in terms of accuracy and computation time.
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Maeda, Noriyoshi, and Tetsuo Shoji. "Failure Probability Analysis by Probabilistic Fracture Mechanics Based on FRI SCC Model." In ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/pvp2010-25917.
Failure Probability of a weld by stress corrosion cracking (SCC) in austenitic stainless steel piping was analyzed by probabilistic fracture mechanics (PFM) approach based on electro-chemical crack growth model (FRI model). In this model, crack growth rate da/dt where a is crack depth is anticipated as the rate of chemical corrosion process defined by electro-chemical Coulomb’s law. The process is also related to the strain rate at the crack tip, taking small scale yielding condition into consideration. Derived transcendental equation is solved numerically by iterative method. Compared to the mechanical crack growth equation like Paris’ law for SCC, FRI model can introduce many electro-chemical parameters such as electric current associated with corrosion of newly born SCC crack surface, the frequency of protective film break and mechanical parameters such as stress intensity factor change with time dK/dt. Stratified Monte-Carlo method was introduced which define the cell of sampling space by the ranges of a/c (c is crack length at surface) and the width of K of sampling space, Kw which has to be defined referring to KSCC below which no SCC is caused. Log-normal distributions were anticipated for a/c distribution and K distribution. Parameter survey performed shows that failure probability which is defined as the ratio of crack number whose depth reached 80% of wall thickness to the total crack number depends on many parameters introduced, especially on yielding stress, electric current decay parameter m, strain hardening index n in Ramberg-Osgood equation and dK/dt. From the requirements of FRI model, two types of threshold value of initial crack depth, cracks having smaller depth than this value can not grow, are proposed. Calculated failure probability does not reach 1 when cracks having smaller initial depth than the threshold value are included in the distribution of analyzing cracks.
