Virtual MRI

Hackländer, T; Mertens, Heinrich

doi:10.1016/j.acra.2004.09.011

Cited by 20 publications

(9 citation statements)

References 5 publications

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“…In turn, this stimulated development of dedicated software solutions that take advantage of growing availability of high-performance computing to increase fidelit of MRI simulations. The existing simulators comprise largely distinct sets of functionalities including basic MRI simulations [ 3 ], simulations in the presence of various imaging system imperfections [ 4 - 6 ], and evaluation of object-fiel interactions for optimization of specifi absorption rate (SAR), and multichannel transmission [ 7 ]. Several simulators feature graphical development interface for pulse sequence design [ 5 , 8 - 10 ] and MRI technique prototyping [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

Liu

Velikina

Block

et al. 2017

IEEE Trans. Med. Imaging

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We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

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Section: Introductionmentioning

confidence: 99%

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

Liu

Velikina

Block

et al. 2017

IEEE Trans. Med. Imaging

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“…A controlled environment would be needed where other parameters (e.g., noise, motion, and image registration) are kept unaltered and where scan duration due to running many protocols do not pose severe practical limitations on patient inclusion. During recent years, numerous studies presented numerical “virtual” MRI is an effective new methodology to achieve such a controlled environment [ 21 – 23 ]. Through modeling MR physics (i.e., solving the Bloch equations) guided by scanner-properties, an input geometry with pre-assigned MR properties (e.g., magnetization, relaxation times), and a pulse sequence, one can computer-simulate an in vivo MR image.…”

Section: Introductionmentioning

confidence: 99%

A Computer-Simulation Study on the Effects of MRI Voxel Dimensions on Carotid Plaque Lipid-Core and Fibrous Cap Segmentation and Stress Modeling

et al. 2015

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BackgroundThe benefits of a decreased slice thickness and/or in-plane voxel size in carotid MRI for atherosclerotic plaque component quantification accuracy and biomechanical peak cap stress analysis have not yet been investigated in detail because of practical limitations.MethodsIn order to provide a methodology that allows such an investigation in detail, numerical simulations of a T1-weighted, contrast-enhanced, 2D MRI sequence were employed. Both the slice thickness (2 mm, 1 mm, and 0.5 mm) and the in plane acquired voxel size (0.62x0.62 mm2 and 0.31x0.31 mm2) were varied. This virtual MRI approach was applied to 8 histology-based 3D patient carotid atherosclerotic plaque models.ResultsA decreased slice thickness did not result in major improvements in lumen, vessel wall, and lipid-rich necrotic core size measurements. At 0.62x0.62 mm2 in-plane, only a 0.5 mm slice thickness resulted in improved minimum fibrous cap thickness measurements (a 2–3 fold reduction in measurement error) and only marginally improved peak cap stress computations. Acquiring voxels of 0.31x0.31 mm2 in-plane, however, led to either similar or significantly larger improvements in plaque component quantification and computed peak cap stress.ConclusionsThis study provides evidence that for currently-used 2D carotid MRI protocols, a decreased slice thickness might not be more beneficial for plaque measurement accuracy than a decreased in-plane voxel size. The MRI simulations performed indicate that not a reduced slice thickness (i.e. more isotropic imaging), but the acquisition of anisotropic voxels with a relatively smaller in-plane voxel size could improve carotid plaque quantification and computed peak cap stress accuracy.

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“…In synthetic MR, the T 1 , T 2 , B 1 field, and proton density are quantified so that images of arbitrary T E , T R , and flip angle a can be synthesized for T 1 -weighted or T 2 -weighted images. [59][60][61] In conclusion, synthetic CT is a powerful tool for simulating arbitrary low dose CT protocols. An initial dual energy scan provides all the information necessary to synthesize raw projections for single energy protocols or material decompositions for dual energy protocols, enabling the imaging performance of a vast array of protocols to be visualized.…”

Section: Discussionmentioning

confidence: 98%

Synthetic CT: Simulating low dose single and dual energy protocols from a dual energy scan

Wang

Pelc

2011

Med. Phys.

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Virtual MRI

Cited by 20 publications

References 5 publications

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

A Computer-Simulation Study on the Effects of MRI Voxel Dimensions on Carotid Plaque Lipid-Core and Fibrous Cap Segmentation and Stress Modeling

Synthetic CT: Simulating low dose single and dual energy protocols from a dual energy scan

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