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SUNMONTUEWEDTHUFRISAT
Events for June 01, 2006
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Recent Developments in Continuously Moving Table Peripheral MR Angiography and Contrast-Enhanced Int
Thu, Jun 01, 2006 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: H. Harry Hu, Ph.D., Mayo Clinic College of Medicine, Magnetic Resonance Laboratory, Rochester, MinnesotaAbstract:
Under the direction of Dr. Stephen J. Riederer, our group's primary focus over the past five years has been contrast-enhanced MR angiography (CE-MRA) with parallel imaging and partial Fourier acquisition methods. My presentation will be divided into two parts. The first portion is technically oriented. I will review a method of continuously moving table (CMT) MRI developed in our laboratory, discuss some of the technical challenges in its implementation, and provide the motivation for using CMT in peripheral CE-MRA. A collection of in vivo clinical results will be shown, not only from the original CMT approach conceived in 2002, but also from recent developments that have incorporated non-traditional k-sampling trajectories and dynamic variations in scanner table velocity and acquisition field-of-view. The second portion of the talk is clinically driven, focusing on the collaborations between our research group and Mayo's clinicians to improve the institution's MR radiology practice. Our most recent project has involved 3D CE-MRA of the lower-legs and 3D contrast-enhanced MR venography (CE-MRV). In the latter, intracranial CE-MRV requires an imaging volume that encompasses the full anterior/posterior and right/left extent of the brain with sub-millimeter spatial resolution for accurate visualization of the venous system. At our institution, these specifications can easily push acquisition times over 4 minutes, well beyond the duration of the administered contrast bolus. CE-MRV is thus an ideal candidate for accelerated MR acquisition techniques such as parallel imaging and partial Fourier. Representative examples from several clinical studies will be shown, where four to nine-fold accelerated acquisitions (30 to 60 seconds) achieved with 2D-SENSE, 2D partial Fourier, and the combination of both, yield results that are rated as either superior or equivalent to corresponding non-accelerated scans for diagnostic image quality by evaluating radiologists.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Kaleena Richards
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Early Warning System for Landslide Predictions using Wireless Sensor Networks
Thu, Jun 01, 2006 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Every year landslides cause heavy loss of life and property particularly in areas that are prone to heavy monsoon. Hence, there is a major need to develop technology that can provide early warning. In this talk we will describe the architecture and preliminary results of using Wireless Sensor Network (WSN) to predict landslides. Primary advantages of using WSN for landslide prediction are: (i) dense data, (ii) overall increased accuracy and robustness because of the dense deployment of sensors,(iii) real-time monitoring and prediction of events and (iv)inexpensive with respect to ease of deployment. In the rocky western (Konkan) coast of India landslides are mainly caused by the increase in strain due to rain water logging in rocks joints, fissures, cavities, causing rocks to decompose and slide down the slope. Existing solutions are expensive and not that accurate.
These methods involve use of expensive equipment like extensometers, tilt sensors, and displacement sensors. In all these, one needs to drill deep holes (approximately 30 meters) to install these sensors. Cost and deployment difficulty preclude dense deployment. We propose a method wherein each node consists of an /inexpensive strain gauge/, a wireless senor node (mote), a mini data acquisition card, and a small size battery. The strain gauge is mounted on the surface of the rock (using few centimeter indentations in the rock) and measures fine rock movement due to built up pressure. We have developed a new algorithm called /CAMP/ / (Clustering and Multi-hop Protocol)/for distributed clustering and multi-hop routing. We also present different distributed hypothesis testing algorithms for deciding the occurrence or non-occurrence of landslides.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Shane Goodoff
