0000000001167238

AUTHOR

Michael Tesch

showing 7 related works from this author

Optimizing MRI contrast with B1 pulses using optimal control theory

2016

The variety of achievable contrasts by MRI makes it a highly flexible and valuable diagnostic tool. Contrast results from relaxation time differences, which are intrinsic properties of each tissue. Using optimal control theory, one can control the obtained contrast by applying excitation pulses that bring the magnetization in a user-defined target state. Simulation results are presented to illustrate the feasibility and the flexibility of using optimal contrast pulses. The robustness to experimental variable parameters such as field inhomogeneities is also studied. Finally, an in-vitro contrast experiment is performed on a small-animal MRI showing a reasonable match with the simulation resu…

0209 industrial biotechnologyComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingContrast (statistics)02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingOptimal control01 natural sciences[SPI.AUTO]Engineering Sciences [physics]/AutomaticMagnetization020901 industrial engineering & automationRobustness (computer science)[ SPI.AUTO ] Engineering Sciences [physics]/Automatic0103 physical sciences010306 general physicsAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingExcitationSimulation[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingComputingMilieux_MISCELLANEOUS
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Optimal control design of preparation pulses for contrast optimization in MRI

2017

Abstract This work investigates the use of MRI radio-frequency (RF) pulses designed within the framework of optimal control theory for image contrast optimization. The magnetization evolution is modeled with Bloch equations, which defines a dynamic system that can be controlled via the application of the Pontryagin Maximum Principle (PMP). This framework allows the computation of optimal RF pulses that bring the magnetization to a given state to obtain the desired contrast after acquisition. Creating contrast through the optimal manipulation of Bloch equations is a new way of handling contrast in MRI, which can explore the theoretical limits of the system. Simulation experiments carried out…

Nuclear and High Energy PhysicsComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingComputationRF pulsesBiophysics010402 general chemistry01 natural sciencesBiochemistry030218 nuclear medicine & medical imaging03 medical and health sciencesMagnetizationMice0302 clinical medicineOpticsRobustness (computer science)Image Interpretation Computer-AssistedImage Processing Computer-AssistedAnimalsComputer SimulationGray MatterMuscle Skeletal[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imagingbusiness.industryPhantoms ImagingContrast (statistics)BrainReproducibility of ResultsContrastCondensed Matter PhysicsOptimal controlImage EnhancementBloch equationsMagnetic Resonance ImagingWhite Matter0104 chemical sciencesWeightingRatsOptimal control[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismOptimal control designBloch equations[ SPI.ELEC ] Engineering Sciences [physics]/ElectromagnetismFemalebusinessAlgorithmAlgorithms
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A simplified framework to optimize MRI contrast preparation

2018

PURPOSE This article proposes a rigorous optimal control framework for the design of preparation schemes that optimize MRI contrast based on relaxation time differences. METHODS Compared to previous optimal contrast preparation schemes, a drastic reduction of the optimization parameter number is performed. The preparation scheme is defined as a combination of several block pulses whose flip angles, phase terms and inter-pulse delays are optimized to control the magnetization evolution. RESULTS The proposed approach reduces the computation time of B 0 -robust preparation schemes to around a minute (whereas several hours were required with previous schemes), with negligible performance loss. …

AgingMultiple Sclerosis[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingComputer scienceComputationContrast MediaContext (language use)HippocampusCorpus Callosum030218 nuclear medicine & medical imagingReduction (complexity)Magnetics03 medical and health sciences0302 clinical medicineThalamusAlzheimer Disease[INFO.INFO-IM]Computer Science [cs]/Medical ImagingAnimalsHumansComputer SimulationRadiology Nuclear Medicine and imagingPoint (geometry)Gray MatterComputingMilieux_MISCELLANEOUSBlock (data storage)Flexibility (engineering)Phantoms ImagingBrainContrast (statistics)Models TheoreticalOptimal controlMagnetic Resonance ImagingRatsFemaleAlgorithmAlgorithms030217 neurology & neurosurgeryMagnetic Resonance in Medicine
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A Simplified Framework for Contrast Optimization in MRI

2018

International audience

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-IM] Computer Science [cs]/Medical Imaging[INFO.INFO-IM]Computer Science [cs]/Medical ImagingComputingMilieux_MISCELLANEOUS
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Optimal Control Pulse Design for Contrast in MRI: in vivo applications

2017

International audience; Optimal control RF pulse design has recently been proposed to address the optimization of image contrast in MRI - in order to explore the theoretical contrast bound of a given imaged system. Their use has recently been validated on a real MRI scanner to contrast various in vitro samples. This abstract extends these results to in vivo applications, and shows that contrasts obtained with standard weighting strategies on rat and mouse brains can be improved or inverted. This demonstrates both the interest and flexibility that one can get when using optimal contrast pulses for in vitro and in vivo applications.

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging
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Optimizing MRI contrast with optimal control theory

2016

International audience; Magnetic Resonance Imaging (MRI) uses the difference in tissue relaxation times to create contrast. Various image weightings can be obtained by tuning acquisition parameters which are usually empirically defined. In this article, optimal control theory is used to design excitation pulses that produce the optimal contrast between given tissues. The designed pulses are tested on numerical phantoms with and without magnetic field inhomogeneities and for the first time in vitro on a small-animal MRI. The reasonable match between simulation and real experiments is promising for the development of such pulses in further in vivo applications.

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingPhysics::Medical Physics[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging
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Contrast Preparation Pulses Robust to B1 and B0 inhomogeneities: an Optimal Control Approach

2018

International audience

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMilieux_MISCELLANEOUS
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