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Whitaker ST, Nataraj G, Nielsen JF, Fessler JA. Myelin water fraction estimation using small-tip fast recovery MRI. Magn Reson Med 2020; 84:1977-1990. [PMID: 32281179 PMCID: PMC7478173 DOI: 10.1002/mrm.28259] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 02/05/2020] [Accepted: 02/26/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE To demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain. METHODS We optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK. RESULTS In simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map. CONCLUSIONS The optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.
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Affiliation(s)
- Steven T. Whitaker
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Gopal Nataraj
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jon-Fredrik Nielsen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey A. Fessler
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
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Guo S, Noll DC. Oscillating steady-state imaging (OSSI): A novel method for functional MRI. Magn Reson Med 2020; 84:698-712. [PMID: 31912574 DOI: 10.1002/mrm.28156] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 11/12/2019] [Accepted: 12/10/2019] [Indexed: 11/08/2022]
Abstract
PURPOSE Signal-to-noise ratio (SNR) is crucial for high-resolution fMRI; however, current methods for SNR improvement are limited. A new approach, called oscillating steady-state imaging (OSSI), produces a signal that is large and T 2 ∗ -weighted, and is demonstrated to produce improved SNR compared to gradient echo (GRE) imaging with matched effective TE and spatial-temporal acquisition characteristics for high-resolution fMRI. METHODS Quadratic phase sequences were combined with balanced gradients to produce a large, oscillating steady-state signal. The quadratic phase progression was periodic over short intervals such as 10 TRs, inducing a frequency-dependent phase dispersal. Images over one period were combined to produce a single image with effectively T 2 ∗ -weighting. The OSSI parameters were explored through simulation and phantom data, and 2D and 3D human fMRI data were collected using OSSI and GRE imaging. RESULTS Phantom and human OSSI data showed highly reproducible signal oscillations with greater signal strength than GRE. Compared to single slice GRE with matched effective TE and spatial-temporal resolution, OSSI yielded more activation in the visual cortex by a factor of 1.84 and an improvement in temporal SNR by a factor of 1.83. Voxelwise percentage change comparisons between OSSI and GRE demonstrate a similar T 2 ∗ -weighted contrast mechanism with additional T 2 ' -weighting of about 15 ms immediately after the RF pulse. CONCLUSIONS OSSI is a new acquisition method that exploits a large, oscillating signal that is T 2 ∗ -weighted and suitable for fMRI. The steady-state signal from balanced gradients creates higher signal strength than single slice GRE at varying TEs, enabling greater volumes of functional activity and higher SNR for high-resolution fMRI.
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Affiliation(s)
- Shouchang Guo
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
| | - Douglas C Noll
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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Wang S, Yang M, Du S, Yang J, Liu B, Gorriz JM, Ramírez J, Yuan TF, Zhang Y. Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning. Front Comput Neurosci 2016; 10:106. [PMID: 27807415 PMCID: PMC5069288 DOI: 10.3389/fncom.2016.00106] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 09/28/2016] [Indexed: 12/17/2022] Open
Abstract
HighlightsWe develop computer-aided diagnosis system for unilateral hearing loss detection in structural magnetic resonance imaging. Wavelet entropy is introduced to extract image global features from brain images. Directed acyclic graph is employed to endow support vector machine an ability to handle multi-class problems. The developed computer-aided diagnosis system achieves an overall accuracy of 95.1% for this three-class problem of differentiating left-sided and right-sided hearing loss from healthy controls.
Aim: Sensorineural hearing loss (SNHL) is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. Materials: We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany). The subjects contain 14 patients with right-sided hearing loss (RHL), 15 patients with left-sided hearing loss (LHL), and 20 healthy controls (HC). Method: We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE) was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM). Results: The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. Conclusions: This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss.
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Affiliation(s)
- Shuihua Wang
- School of Electronic Science and Engineering, Nanjing UniversityNanjing, China; School of Computer Science and Technology, Nanjing Normal UniversityNanjing, China; Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police AcademyChangsha, China
| | - Ming Yang
- Department of Radiology, Nanjing Children's Hospital, Nanjing Medical UniversityNanjing, China; Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University, Quanzhou Normal UniversityQuanzhou, China
| | - Sidan Du
- School of Electronic Science and Engineering, Nanjing University Nanjing, China
| | - Jiquan Yang
- Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing, China
| | - Bin Liu
- Department of Radiology, Zhong-Da Hospital of Southeast University Nanjing, China
| | - Juan M Gorriz
- Department of Signal Theory, Networking and Communications, University of Granada Granada, Spain
| | - Javier Ramírez
- Department of Signal Theory, Networking and Communications, University of Granada Granada, Spain
| | - Ti-Fei Yuan
- School of Computer Science and Technology, Nanjing Normal UniversityNanjing, China; State Key Lab of CAD & CG, Zhejiang UniversityHangzhou, China
| | - Yudong Zhang
- School of Computer Science and Technology, Nanjing Normal UniversityNanjing, China; Key Laboratory of Statistical Information Technology and Data Mining, State Statistics BureauChengdu, China
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Sun H, Fessler JA, Noll DC, Nielsen JF. Joint Design of Excitation k-Space Trajectory and RF Pulse for Small-Tip 3D Tailored Excitation in MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2016; 35:468-79. [PMID: 26390450 PMCID: PMC4792784 DOI: 10.1109/tmi.2015.2478880] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
We propose a new method for the joint design of k-space trajectory and RF pulse in 3D small-tip tailored excitation. Designing time-varying RF and gradient waveforms for a desired 3D target excitation pattern in MRI poses a non-linear, non-convex, constrained optimization problem with relatively large problem size that is difficult to solve directly. Existing joint pulse design approaches are therefore typically restricted to predefined trajectory types such as EPI or stack-of-spirals that intrinsically satisfy the gradient maximum and slew rate constraints and reduce the problem size (dimensionality) dramatically, but lead to suboptimal excitation accuracy for a given pulse duration. Here we use a 2nd-order B-spline basis that can be fitted to an arbitrary k-space trajectory, and allows the gradient constraints to be implemented efficiently. We show that this allows the joint optimization problem to be solved with quite general k-space trajectories. Starting from an arbitrary initial trajectory, we first approximate the trajectory using B-spline basis, and then optimize the corresponding coefficients. We evaluate our method in simulation using four different k-space initializations: stack-of-spirals, SPINS, KT-points, and a new method based on KT-points. In all cases, our approach leads to substantial improvement in excitation accuracy for a given pulse duration. We also validated our method for inner-volume excitation using phantom experiments. The computation is fast enough for online applications.
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Affiliation(s)
- Hao Sun
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jeffrey A. Fessler
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USA
| | - Douglas C. Noll
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jon-Fredrik Nielsen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109 USA
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SUN HAO, FESSLER JEFFREYA, NOLL DOUGLASC, NIELSEN JONFREDRIK. Balanced SSFP-like steady-state imaging using small-tip fast recovery with a spectral prewinding pulse. Magn Reson Med 2016; 75:839-44. [PMID: 25820494 PMCID: PMC4587989 DOI: 10.1002/mrm.25682] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Revised: 01/16/2015] [Accepted: 02/11/2015] [Indexed: 11/06/2022]
Abstract
PURPOSE Small-tip fast recovery (STFR) imaging has been proposed recently as a potential alternative to balanced steady-state free precession (bSSFP). STFR relies on a tailored "tip-up" radio-frequency pulse to achieve comparable signal level as bSSFP, but with reduced banding artifacts and transient oscillations, and is compatible with magnetization-preparation pulses. Previous STFR implementations used two-dimensional or three-dimensional pulses spatially tailored to the accumulated phase calculated from a B0 field map, making the steady-state STFR signal contain some T2* weighting. Here, we propose to replace the spatially tailored pulse with a recently introduced spectrally selective "pre-winding" pulse that is precomputed to a target frequency range. The proposed "spectral-STFR" sequence produces T2/T1-weighted images similar to bSSFP, but with reduced banding and potentially other benefits. THEORY AND METHODS We investigated the steady-state signal properties of spectral-STFR using simulations, and phantom and human volunteer experiments. RESULTS Our simulation and experimental results showed that the spectral-STFR sequence has similar signal level and tissue contrast as bSSFP, but has a wider passband and more consistent banding profiles across different tissues (e.g., less hyperintense signal at band edges for low flip angles). Care is needed in designing the spectral radio-frequency pulse to ensure that the small tip angle approximation holds during radio-frequency transmission. CONCLUSION Spectral-STFR has similar tissue contrast as bSSFP but a wider passband and more consistent cerebrospinal fluid/brain tissue contrast across the passband. The spectral-STFR sequence is a potential alternative to bSSFP in some applications. Compared to a spatially tailored STFR sequence, spectral-STFR can be precomputed, is easier to implement in practice, and potentially has more uniform image contrast and minimal T2* weighting.
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Affiliation(s)
- HAO SUN
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
| | - JEFFREY A. FESSLER
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - DOUGLAS C. NOLL
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - JON-FREDRIK NIELSEN
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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Sun H, Fessler JA, Noll DC, Nielsen JF. Rapid inner-volume imaging in the steady-state with 3D selective excitation and small-tip fast recovery imaging. Magn Reson Med 2015; 76:1217-23. [PMID: 26507586 DOI: 10.1002/mrm.26026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 09/30/2015] [Accepted: 10/03/2015] [Indexed: 12/23/2022]
Abstract
PURPOSE Develop a method for rapid three-dimensional inner-volume (IV), or reduced field-of-view, steady-state imaging. METHODS Tailored radiofrequency pulses for exciting a three-dimensional IV were designed using a recently proposed algorithm and used in three different sequences: spoiled gradient echo, balanced steady-state free precession, and "small-tip fast recovery" (STFR) which uses a "tip-up" RF pulse after the readout to fast recover spins to the longitudinal axis. The inner- and outer-volume (OV) steady-state signals were analyzed. To demonstrate the potential utility of the proposed method, segmented stack-of-spirals reduced field-of-view images in a volunteer were acquired. RESULTS For a given three-dimensional IV excitation pulse, STFR can achieve higher IV/OV signal ratio compared with spoiled gradient echo and balanced steady-state free precession. For spoiled gradient echo and balanced steady-state free precession, this ratio is significantly lower than that produced by a single IV excitation. For STFR, this ratio exceeds that produced by a single IV excitation, due to partial OV saturation produced by the nonspatially selective tip-up pulse. Reduced FOV STFR stack-of-spirals imaging with 2-fold under-sampling in both x-y and z is demonstrated. CONCLUSION STFR provides an effective mechanism for OV suppression in steady-state IV imaging. The recently proposed joint pulse design method can be used in the STFR sequence to achieve fast reduced field-of-view imaging. Magn Reson Med 76:1217-1223, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Hao Sun
- Departments of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey A Fessler
- Departments of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA.,Departments of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Douglas C Noll
- Departments of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Jon-Fredrik Nielsen
- Departments of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
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Longo MG, Vairo F, Souza CF, Giugliani R, Vedolin LM. Brain imaging and genetic risk in the pediatric population, part 1: inherited metabolic diseases. Neuroimaging Clin N Am 2015; 25:31-51. [PMID: 25476511 DOI: 10.1016/j.nic.2014.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
In this article, the genotype-MR phenotype correlation of the most common or clinically important inherited metabolic diseases (IMD) in the pediatric population is reviewed. A nonsystematic search of the PubMed/Medline database of relevant studies about "genotype-phenotype correlation" in IMD was performed. Some MR phenotypes related to specific gene mutations were found, such as bilateral hypertrophy of inferior olives in patients harboring POLG and SURF1 mutations, and central lesions in the cervical spinal cord in patients with nonketotic hyperglycinemia harboring GLRX5 gene mutation.
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Affiliation(s)
- Maria Gabriela Longo
- Radiology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Filippo Vairo
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post Graduation Program on Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Carolina Fischinger Souza
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Roberto Giugliani
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Leonardo Modesti Vedolin
- Radiology Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post Graduation Program on Medical Sciences: Medicine, Department of Internal Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
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Jou T, Patterson S, Pauly JM, Bowen CV. Fat-suppressed alternating-SSFP for whole-brain fMRI using breath-hold and visual stimulus paradigms. Magn Reson Med 2015; 75:1978-88. [PMID: 26037220 DOI: 10.1002/mrm.25797] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 04/24/2015] [Accepted: 05/01/2015] [Indexed: 11/07/2022]
Abstract
PURPOSE To achieve artifact-suppressed whole-brain pass-band-balanced steady-state free precession functional MRI from a single functional magnetic resonance imaging (fMRI) scan. METHODS A complete and practical data acquisition sequence for alt-SSFP fMRI was developed. First, multishot flyback-echo-planar imaging (EPI) and echo-time shifting were used to achieve data acquisition that was robust against eddy currents, gradient delays, and ghosting artifacts. Second, a steady-state catalyzation scheme was implemented to reduce oscillations in the transient signal when catalyzing in and out of alternate steady states. Next, a short spatial-spectral radiofrequency (RF) pulse was designed to achieve excellent fat-suppression while maintaining a repetition time <15 ms to sensitize functional activation toward smaller vessels and capillaries. Lastly, parallel imaging was used to achieve whole-brain coverage and sufficiently high temporal resolution. RESULTS Breath-hold experiments showed excellent fat-suppression and alt-SSFP's capability to recover functional sensitivity from signal dropout regions of conventional gradient-echo and banding artifacts from conventional pass-band-balanced steady-state free precession. Applying fat-suppression resulted in improved activation maps and increased temporal SNR. Visual stimulus functional studies verify the proposed method's excellent functional sensitivity to neuronal activation. CONCLUSION Artifact-suppressed images are demonstrated, showing a practical pass-band-balanced steady-state free precession fMRI method that permits whole-brain imaging with excellent blood oxygen level-dependent sensitivity and fat suppression.
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Affiliation(s)
- Tiffany Jou
- Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Steve Patterson
- Biomedical Translational Imaging Centre, Halifax, Nova Scotia, Canada
| | - John M Pauly
- Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Chris V Bowen
- Department of Radiology, Dalhousie University, Halifax, Nova Scotia, Canada
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Zhao F, Nielsen JF, Swanson SD, Fessler JA, Noll DC. Simultaneous fat saturation and magnetization transfer contrast imaging with steady-state incoherent sequences. Magn Reson Med 2014; 74:739-46. [PMID: 25252173 DOI: 10.1002/mrm.25475] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 09/01/2014] [Accepted: 09/04/2014] [Indexed: 11/10/2022]
Abstract
PURPOSE This work combines an n-dimensional fat sat(uration) radiofrequency (RF) pulse with steady-state incoherent (SSI) pulse sequences, e.g., spoiled gradient-echo sequence, to simultaneously produce B0 insensitive fat suppression and magnetization transfer (MT) contrast. This pulse is then referred to as "fat sat and MT contrast pulse." THEORY We discuss the features of the fat sat and MT contrast pulse and the MT sensitivities of the SSI sequences when combining with fat sat. Moreover, we also introduce an adapted RF spoiling scheme for SSI sequences with fat sat. METHODS Simulations and phantom experiments were conducted to demonstrate the adapted RF spoiling. Fat suppression and MT effects are shown in 3T phantom experiments and in vivo experiments, including brain imaging, cartilage imaging, and angiography. RESULTS To ensure that the sequence reaches steady state, the adapted RF spoiling is required for fat sat SSI sequences. Fat sat and MT contrast pulse works robustly with field inhomogeneity and also produces MT contrasts. CONCLUSION SSI sequences with fat sat and MT contrast pulse and adapted RF spoiling can robustly produce fat suppressed and MT contrast images in the presence of field inhomogeneity.
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Affiliation(s)
- Feng Zhao
- Biomedical Engineering Department, The University of Michigan, Ann Arbor, Michigan, USA
| | - Jon-Fredrik Nielsen
- Biomedical Engineering Department, The University of Michigan, Ann Arbor, Michigan, USA
| | - Scott D Swanson
- Radiology Department, The University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey A Fessler
- Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan, USA
| | - Douglas C Noll
- Biomedical Engineering Department, The University of Michigan, Ann Arbor, Michigan, USA
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