Zoom Meeting (Information posted at the end of the announcement)
Spatiotemporal encoding methods for brain magnetic resonance imaging
Magnetic resonance imaging (MRI) is a widely used non-invasive imaging technology for both clinical diagnosis and neuroscientific research. However, the imaging sensitivity and specificity of brain MRI are limited by the well-known technical challenge of MRI acquisition—low image encoding efficiency, leading to limited acquisition speed, spatial resolution and signal-to-noise ratio especially for in-vivo imaging.
In order to address these challenges, this thesis presents our newly developed spatiotemporal encoding methods, which are then tailored to improve the acquisition efficiency of different MRI applications, including quantitative relaxometry, functional and diffusion imaging. The novel encoding strategies in the high-dimensional space, together with efficient data sampling schemes, allow better use of radio-frequency pulse, modern receiver coil arrays and shared data correlation to achieve unprecedented acceleration capability.
We demonstrate that the significantly improved imaging efficiency enables ultra-fast multi-parametric mapping at submillimeter isotropic resolution with an order-of-magnitude faster acquisition speed, as well as functional MRI with higher neuronal specificity. The future application of the proposed techniques should improve the diagnosis power of clinical brain MRI and allow further understanding of the structural and functional organization of the human brain.
Thesis Supervisor:
Kawin Setsompop, PhD
Associate Professor of Radiology, Stanford University
Thesis Committee Chair:
Elfar Adalsteinsson, PhD
Professor of Electrical Engineering and Computer Science, MIT
Professor of Institute for Medical Engineering and Science, MIT
Thesis Readers:
Lawrence Wald, PhD
Professor of Radiology, MGH, HMS
Bruce Rosen, MD, PhD
Laurence Lamson Robbins Professor of Radiology, MGH, HMS
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Zoom invitation -
Fuyixue Wang is inviting you to a scheduled Zoom meeting.
Topic: Fuyixue Wang Thesis Defense
Time: May 13, 2021 03:00 PM Eastern Time (US and Canada)
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