Technical Program

Paper Detail

Paper:	SA-AM-OS1.4
Session:	MRI Acquisition and Reconstruction
Time:	Saturday, April 8, 10:30 - 10:50
Presentation:	Oral
Title:	Regularized Inversion of Noisy, Incomplete MR Spectroscopic Imaging Data with Anatomical Prior
Authors:	Justin Haldar; University of Illinois at Urbana-Champaign
	Mathews Jacob; University of Illinois at Urbana-Champaign
	Andreas Ebel; University of California, San Francisco
	Xiaoping Zhu; University of California, San Francisco
	Norbert Schuff; University of California, San Francisco
	Diego Hernando; University of Illinois at Urbana-Champaign
	Bradley Sutton; University of Illinois at Urbana-Champaign
	Zhi-Pei Liang; University of Illinois at Urbana-Champaign
Abstract:	This paper addresses the image reconstruction problem in MR spectroscopic imaging experiments where noisy, limited Fourier data are often collected due to temporal constraints. A parametric method is proposed which is capable of incorporating exact and uncertain boundary information. Experimental results show that the technique can generate metabolic images with much higher spatial resolution than the conventional Fourier method and existing constrained reconstruction methods.

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