Accelerating T2* Mapping with Maximum Likelihood Estimation (MLE) and Parallel Imaging(PI)

Wajiha Bano, Arnold Julian Vinoj Benjamin, Ian Marshall, Michael Davies

Research output: Contribution to conferenceAbstractpeer-review

Abstract

The utility of MR parametric mapping is limited due to the lengthy acquisition time. A Maximum Likelihood Estimation (MLE) and Parallel Imaging
(PI) method is presented for MR parameteric mapping. The approach is based on a high Signal to Noise ratio (SNR) assumption such that the noise
can be modelled as Gaussian and estimates the parameters that maximizes the signal from a multichannel coil. The method was tested on a multiecho
gradient-echo T2* mapping experiment in a phantom and a human brain. Accurate T2* maps were reconstructed up to an acceleration factor
of 6 with a small error for phantom and human brain.
Original languageEnglish
Publication statusPublished - 21 Apr 2017
EventISMRM 25th Annual Meeting - Hawaii, Honolulu, United States
Duration: 22 Apr 201727 Apr 2017
https://www.ismrm.org/2017-annual-meeting-exhibition/

Conference

ConferenceISMRM 25th Annual Meeting
CountryUnited States
CityHonolulu
Period22/04/1727/04/17
Internet address

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