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Fast, variable system delay correction for spiral MRI

Description

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

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.

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Agent

Created

Date Created
2013

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NVM challenges in medical devices

Description

Electronic devices are gaining an increasing market share in the medical field. Medical devices are becoming more sophisticated, and encompassing more applications. Unlike consumer electronics, medical devices have far more limitations when it comes to area, power and most importantly

Electronic devices are gaining an increasing market share in the medical field. Medical devices are becoming more sophisticated, and encompassing more applications. Unlike consumer electronics, medical devices have far more limitations when it comes to area, power and most importantly reliability. The medical devices industry has recently seen the advantages of using Flash memory instead of Read Only Memory (ROM) for firmware storage, and in some cases to replace Electrically Programmable Read Only Memories (EEPROMs) in medical devices for frequent data storage. There are direct advantages to using Flash memory instead of Read Only Memory, most importantly the fact that firmware can be rewritten along the development cycle and in the field. However, Flash technology requires high voltage circuitry that makes it harder to integrate into low power devices. There have been a lot of advances in Non-Volatile Memory (NVM) technologies, and many Flash rivals are starting to gain attention. The purpose of this thesis is to evaluate these new technologies against Flash to determine the feasibility as well as the advantages of each technology. The focus is on embedded memory in a medical device micro-controller and application specific integrated circuits (ASIC). A behavioral model of a Programmable Metallization Cell (PMC) was used to simulate the behavior and determine the advantages of using PMC technology versus flash. When compared to flash test data, PMC based embedded memory showed a reduction in power consumption by many orders of magnitude. Analysis showed that an approximated 20% device longevity increase can be achieved by using embedded PMC technology.

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Agent

Created

Date Created
2010