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Rusho RZ, Ahmed AH, Kruger S, Alam W, Meyer D, Howard D, Story B, Jacob M, Lingala SG. Prospectively accelerated dynamic speech magnetic resonance imaging at 3 T using a self-navigated spiral-based manifold regularized scheme. NMR IN BIOMEDICINE 2024; 37:e5135. [PMID: 38440911 DOI: 10.1002/nbm.5135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 03/06/2024]
Abstract
This work develops and evaluates a self-navigated variable density spiral (VDS)-based manifold regularization scheme to prospectively improve dynamic speech magnetic resonance imaging (MRI) at 3 T. Short readout duration spirals (1.3-ms long) were used to minimize sensitivity to off-resonance. A custom 16-channel speech coil was used for improved parallel imaging of vocal tract structures. The manifold model leveraged similarities between frames sharing similar vocal tract postures without explicit motion binning. The self-navigating capability of VDS was leveraged to learn the Laplacian structure of the manifold. Reconstruction was posed as a sensitivity-encoding-based nonlocal soft-weighted temporal regularization scheme. Our approach was compared with view-sharing, low-rank, temporal finite difference, extra dimension-based sparsity reconstruction constraints. Undersampling experiments were conducted on five volunteers performing repetitive and arbitrary speaking tasks at different speaking rates. Quantitative evaluation in terms of mean square error over moving edges was performed in a retrospective undersampling experiment on one volunteer. For prospective undersampling, blinded image quality evaluation in the categories of alias artifacts, spatial blurring, and temporal blurring was performed by three experts in voice research. Region of interest analysis at articulator boundaries was performed in both experiments to assess articulatory motion. Improved performance with manifold reconstruction constraints was observed over existing constraints. With prospective undersampling, a spatial resolution of 2.4 × 2.4 mm2/pixel and a temporal resolution of 17.4 ms/frame for single-slice imaging, and 52.2 ms/frame for concurrent three-slice imaging, were achieved. We demonstrated implicit motion binning by analyzing the mechanics of the Laplacian matrix. Manifold regularization demonstrated superior image quality scores in reducing spatial and temporal blurring compared with all other reconstruction constraints. While it exhibited faint (nonsignificant) alias artifacts that were similar to temporal finite difference, it provided statistically significant improvements compared with the other constraints. In conclusion, the self-navigated manifold regularized scheme enabled robust high spatiotemporal resolution dynamic speech MRI at 3 T.
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Affiliation(s)
- Rushdi Zahid Rusho
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Abdul Haseeb Ahmed
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Stanley Kruger
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Wahidul Alam
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
| | - David Meyer
- Janette Ogg Voice Research Center, Shenandoah University, Winchester, Virginia, USA
| | - David Howard
- Department of Electronic Engineering, Royal Holloway, University of London, London, UK
| | - Brad Story
- Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, Arizona, USA
| | - Mathews Jacob
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Sajan Goud Lingala
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
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Martín-González E, Moya-Sáez E, Menchón-Lara RM, Royuela-Del-Val J, Palencia-de-Lara C, Rodríguez-Cayetano M, Simmross-Wattenberg F, Alberola-López C. A clinically viable vendor-independent and device-agnostic solution for accelerated cardiac MRI reconstruction. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 207:106143. [PMID: 34029830 DOI: 10.1016/j.cmpb.2021.106143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 04/25/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE Recent research has reported methods that reconstruct cardiac MR images acquired with acceleration factors as high as 15 in Cartesian coordinates. However, the computational cost of these techniques is quite high, taking about 40 min of CPU time in a typical current machine. This delay between acquisition and final result can completely rule out the use of MRI in clinical environments in favor of other techniques, such as CT. In spite of this, reconstruction methods reported elsewhere can be parallelized to a high degree, a fact that makes them suitable for GPU-type computing devices. This paper contributes a vendor-independent, device-agnostic implementation of such a method to reconstruct 2D motion-compensated, compressed-sensing MRI sequences in clinically viable times. METHODS By leveraging our OpenCLIPER framework, the proposed system works in any computing device (CPU, GPU, DSP, FPGA, etc.), as long as an OpenCL implementation is available, and development is significantly simplified versus a pure OpenCL implementation. In OpenCLIPER, the problem is partitioned in independent black boxes which may be connected as needed, while device initialization and maintenance is handled automatically. Parallel implementations of both a groupwise FFD-based registration method, as well as a multicoil extension of the NESTA algorithm have been carried out as processes of OpenCLIPER. Our platform also includes significant development and debugging aids. HIP code and precompiled libraries can be integrated seamlessly as well since OpenCLIPER makes data objects shareable between OpenCL and HIP. This also opens an opportunity to include CUDA source code (via HIP) in prospective developments. RESULTS The proposed solution can reconstruct a whole 12-14 slice CINE volume acquired in 19-32 coils and 20 phases, with an acceleration factor of ranging 4-8, in a few seconds, with results comparable to another popular platform (BART). If motion compensation is included, reconstruction time is in the order of one minute. CONCLUSIONS We have obtained clinically-viable times in GPUs from different vendors, with delays in some platforms that do not have correspondence with its price in the market. We also contribute a parallel groupwise registration subsystem for motion estimation/compensation and a parallel multicoil NESTA subsystem for l1-l2-norm problem solving.
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Affiliation(s)
- Elena Martín-González
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
| | - Elisa Moya-Sáez
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
| | - Rosa-María Menchón-Lara
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
| | | | | | - Manuel Rodríguez-Cayetano
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
| | - Federico Simmross-Wattenberg
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
| | - Carlos Alberola-López
- Laboratorio de Procesado de Imagen (Image Processing Laboratory), Universidad de Valladolid, Valladolid 47011, Spain.
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Godino-Moya A, Menchón-Lara RM, Martín-Fernández M, Prieto C, Alberola-López C. Elastic AlignedSENSE for Dynamic MR Reconstruction: A Proof of Concept in Cardiac Cine. ENTROPY 2021; 23:e23050555. [PMID: 33947089 PMCID: PMC8145958 DOI: 10.3390/e23050555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/25/2022]
Abstract
Numerous methods in the extensive literature on magnetic resonance imaging (MRI) reconstruction exploit temporal redundancy to accelerate cardiac cine. Some of them include motion compensation, which involves high computational costs and long runtimes. In this work, we proposed a method—elastic alignedSENSE (EAS)—for the direct reconstruction of a motion-free image plus a set of nonrigid deformations to reconstruct a 2D cardiac sequence. The feasibility of the proposed approach was tested in 2D Cartesian and golden radial multi-coil breath-hold cardiac cine acquisitions. The proposed approach was compared against parallel imaging compressed sense (sPICS) and group-wise motion corrected compressed sense (GWCS) reconstructions. EAS provides better results on objective measures with considerable less runtime when an acceleration factor is higher than 10×. Subjective assessment of an expert, however, invited proposing the combination of EAS and GWCS as a preferable alternative to GWCS or EAS in isolation.
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Affiliation(s)
- Alejandro Godino-Moya
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
- Correspondence:
| | - Rosa-María Menchón-Lara
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
| | - Marcos Martín-Fernández
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK;
- School of Engineering, Pontificia Universidad Catolica de Chile, Santiago 4860, Chile
| | - Carlos Alberola-López
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
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Menchón-Lara RM, Royuela-Del-Val J, Simmross-Wattenberg F, Casaseca-de-la-Higuera P, Martín-Fernández M, Alberola-López C. Fast 4D elastic group-wise image registration. Convolutional interpolation revisited. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 200:105812. [PMID: 33160691 DOI: 10.1016/j.cmpb.2020.105812] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 10/15/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND AND OBJECTIVE This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. METHODS Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. RESULTS The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90%, both in CPU and GPU executions, compared with the classical tensor product formulation. CONCLUSIONS Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.
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Affiliation(s)
- Rosa-María Menchón-Lara
- Laboratorio de Procesado de Imagen. ETSI de Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
| | | | | | | | - Marcos Martín-Fernández
- Laboratorio de Procesado de Imagen. ETSI de Telecomunicación, Universidad de Valladolid, Valladolid, Spain
| | - Carlos Alberola-López
- Laboratorio de Procesado de Imagen. ETSI de Telecomunicación, Universidad de Valladolid, Valladolid, Spain
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Aviles-Rivero AI, Debroux N, Williams G, Graves MJ, Schönlieb CB. Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction. Med Image Anal 2020; 68:101933. [PMID: 33341495 DOI: 10.1016/j.media.2020.101933] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 11/23/2020] [Accepted: 11/27/2020] [Indexed: 10/22/2022]
Abstract
We address the problem of reconstructing high quality images from undersampled MRI data. This is a challenging task due to the highly ill-posed nature of the problem. In particular, in dynamic MRI scans, the interaction between the target structure and the physical motion affects the acquired measurements leading to blurring artefacts and loss of fine details. In this work, we propose a framework for dynamic MRI reconstruction framed under a new multi-task optimisation model called Compressed Sensing Plus Motion (CS + M). Firstly, we propose a single optimisation problem that simultaneously computes the MRI reconstruction and the physical motion. Secondly, we show our model can be efficiently solved by breaking it up into two computationally tractable problems. The potentials and generalisation capabilities of our approach are demonstrated in different clinical applications including cardiac cine, cardiac perfusion and brain perfusion imaging. We show, through numerical experiments, that the proposed scheme reduces blurring artefacts, and preserves the target shape and fine details in the reconstruction. We also report the highest quality reconstruction under high undersampling rates in comparison to several state of the art techniques.
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Affiliation(s)
| | - Noémie Debroux
- Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal, France
| | - Guy Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, UK
| | - Martin J Graves
- Department of Radiology, Cambridge University Hospitals, University of Cambridge, UK
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Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction. ENTROPY 2020; 22:e22060687. [PMID: 33286459 PMCID: PMC7517224 DOI: 10.3390/e22060687] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 12/22/2022]
Abstract
Groupwise image (GW) registration is customarily used for subsequent processing in medical imaging. However, it is computationally expensive due to repeated calculation of transformations and gradients. In this paper, we propose a deep learning (DL) architecture that achieves GW elastic registration of a 2D dynamic sequence on an affordable average GPU. Our solution, referred to as dGW, is a simplified version of the well-known U-net. In our GW solution, the image that the other images are registered to, referred to in the paper as template image, is iteratively obtained together with the registered images. Design and evaluation have been carried out using 2D cine cardiac MR slices from 2 databases respectively consisting of 89 and 41 subjects. The first database was used for training and validation with 66.6–33.3% split. The second one was used for validation (50%) and testing (50%). Additional network hyperparameters, which are—in essence—those that control the transformation smoothness degree, are obtained by means of a forward selection procedure. Our results show a 9-fold runtime reduction with respect to an optimization-based implementation; in addition, making use of the well-known structural similarity (SSIM) index we have obtained significative differences with dGW with respect to an alternative DL solution based on Voxelmorph.
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Kamesh Iyer S, Moon BF, Josselyn N, Ruparel K, Roalf D, Song JW, Guiry S, Ware JB, Kurtz RM, Chawla S, Nabavizadeh SA, Witschey WR. Data-Driven Quantitative Susceptibility Mapping Using Loss Adaptive Dipole Inversion (LADI). J Magn Reson Imaging 2020; 52:823-835. [PMID: 32128914 DOI: 10.1002/jmri.27103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/31/2020] [Accepted: 02/01/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features. PURPOSE To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information. STUDY TYPE Retrospective. SUBJECTS, ANIMAL MODELS A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart. SEQUENCE/FIELD STRENGTH 3D gradient echo sequence on 3T and 7T scanners. ASSESSMENT Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS). STATISTICAL TESTS Bland-Altman, Friedman test, and Conover multiple comparisons. RESULTS Loss adaptive dipole inversion (LADI) (β = 0.82, R2 = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R2 = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R2 = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQGrade = 2.6 ± 0.4, ISGrade = 2.6 ± 0.3, IQRank = 3.5 ± 0.4, ISRank = 3.9 ± 0.2) compared with MEDI (IQGrade = 2.1 ± 0.3, ISGrade = 2 ± 0.5, IQRank = 2.4 ± 0.5, ISRank = 2.8 ± 0.2) and FANSI (IQGrade = 2.2 ± 0.5, ISGrade = 2 ± 0.4, IQRank = 2.8 ± 0.3, ISRank = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (InfMEDI = -0.27 ± 0.06 ppm) was better mitigated by FANSI (InfFANSI-TGV = -0.17 ± 0.05 ppm) and LADI (InfLADI = -0.18 ± 0.05 ppm). CONCLUSION For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM. EVIDENCE LEVEL 4 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:823-835.
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Affiliation(s)
- Srikant Kamesh Iyer
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Brianna F Moon
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicholas Josselyn
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kosha Ruparel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jae W Song
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Samantha Guiry
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jeffrey B Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert M Kurtz
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - S Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Walter R Witschey
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Menchón-Lara RM, Simmross-Wattenberg F, Casaseca-de-la-Higuera P, Martín-Fernández M, Alberola-López C. Reconstruction techniques for cardiac cine MRI. Insights Imaging 2019; 10:100. [PMID: 31549235 PMCID: PMC6757088 DOI: 10.1186/s13244-019-0754-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 05/17/2019] [Indexed: 12/17/2022] Open
Abstract
The present survey describes the state-of-the-art techniques for dynamic cardiac magnetic resonance image reconstruction. Additionally, clinical relevance, main challenges, and future trends of this image modality are outlined. Thus, this paper aims to provide a general vision about cine MRI as the standard procedure in functional evaluation of the heart, focusing on technical methodologies.
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Affiliation(s)
- Rosa-María Menchón-Lara
- Laboratorio de Procesado de Imagen. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad de Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain.
| | - Federico Simmross-Wattenberg
- Laboratorio de Procesado de Imagen. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad de Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain
| | - Pablo Casaseca-de-la-Higuera
- Laboratorio de Procesado de Imagen. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad de Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain
| | - Marcos Martín-Fernández
- Laboratorio de Procesado de Imagen. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad de Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain
| | - Carlos Alberola-López
- Laboratorio de Procesado de Imagen. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad de Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain
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Sanz-Estébanez S, Rabanillo-Viloria I, Royuela-del-Val J, Aja-Fernández S, Alberola-López C. Joint groupwise registration and ADC estimation in the liver using a B-value weighted metric. Magn Reson Imaging 2018; 46:1-9. [DOI: 10.1016/j.mri.2017.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 10/09/2017] [Accepted: 10/10/2017] [Indexed: 12/18/2022]
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