High-resolution MR metabolic imaging.
Magnetic resonance spectroscopic imaging has been recognized for a long time as a powerful tool for biochemical imaging. However, its practical utility is still rather limited due to poor spatial resolution, low signal-to-noise ratio, and long data acquisition times. In this work, we propose a new technique that enables reconstruction of metabolite maps with high spatial resolution. This technique uses a statistical model to incorporate known anatomical boundaries for edge-preserving noise filtering. This statistical reconstruction scheme makes it possible to use very noisy data, thereby enabling the collection of high-resolution data in a reasonable amount of time. We illustrate the performance of this method with images of the N-acetyl-L-aspartate distribution from an in vivo mouse brain.
Haldar
Justin P
JP
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1406 West Green Street, Urbana, IL 61801, USA. haldar@uiuc.edu
Hernando
Diego
D
Budde
Matthew D
MD
Wang
Qing
Q
Song
Sheng-Kwei
SK
Liang
Zhi-Pei
ZP
D000818:Animals; D001224:Aspartic Acid / Q000031:analogs & derivatives* / Q000378:metabolism; D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D051379:Mice; D008954:Models, Biological; D011859:Radiography
D001224:Aspartic Acid; C000179:N-acetylaspartate