Leland Stanford Junior University

Angel R Pineda

Scott Brian Reeder

Huanzhou Yu

Charles McKenzie

Norbert Joseph Pelc

Zhifei Wen

A method of separating signals from at least two species in a body using echo-coherent time magnetic resonance imaging is provided. A plurality of echo signals is acquired at acquisition times optimized based on the noise properties of images with different variance with possibly correlated noise resulting in possibly asymmetrically positioned images with respect to an echo time. The plurality of echo signals is combined iteratively by using a maximum likelihood decomposition algorithm for non-identically distributed noise.

Maximum likelihood estimator in the presence of non-identically distributed noise for decomposition of chemical species in MRI

A method for generating a magnetic resonance images is provided. A magnetic resonance imaging excitation is applied. A plurality of magnetic resonance image signals is acquired. The plurality of image signals is combined iteratively by using a regularized decomposition algorithm. An image created from combining the plurality of image signals iteratively is displayed.

Regularized species separation

A method for generating a magnetic resonance image is provided. A magnetic resonance imaging excitation is applied for a plurality of cycles at a cycle rate. A plurality of magnetic resonance image echoes is acquired for each cycle. A decay map is estimated from the plurality of magnetic resonance image echoes for each cycle. The estimated decay map is used to generate an image for at least two different species.

[object Object]

A method of separating signals from water and lipid in a body using spin-echo magnetic resonance imaging comprising steps of acquiring image signals at three acquisition times asymmetrically positioned with respect to a spin-echo time, the three acquisition times being separated by 2&#x3c0;/3 and the middle signal acquisition is centered at &#x3c0;/2+&#x3c0;k where k is an integer, and combining the plurality of image signals iterative using a least squares decomposition method.

Growing community of inventors

Fullerton, CA, United States of America

Angel R Pineda