Bayesian estimation of MR images from incomplete raw data

被引：0
|
作者：
Marseille, GJ
deBeer, R
Fuderer, M
Mehlkopf, AF
vanOrmondt, D
机构：
来源：
MAXIMUM ENTROPY AND BAYESIAN METHODS - PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL WORKSHOP ON MAXIMUM ENTROPY AND BAYESIAN METHODS, CAMBRIDGE, ENGLAND, 1994 | 1996年 / 70卷
关键词：
magnetic resonance; scan time reduction; optimal non-uniform sampling; Bayesian estimation; image reconstruction;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This work concerns reduction of the MRT, scan time through optimal sampling. We derive optimal sample positions hom Cramer-Rao theory. These positions are nonuniformly distributed, which hampers Fourier transformation to the image domain. With the aid of Bayesian formalism we estimate an image that satisfies prior knowledge while its inverse Fourier transform is compatible with the acquired samples. The new technique is applied successfully to a real-world MRI scan of a human brain.
引用
收藏
页码：13 / 22
页数：4
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