Introduction

PARSE is parameter assesment by retreval from signal encoding. Our goal is the development of an enhanced signal model image reconstruction technique for magnetic resonance imaging. It extends the current k-space based reconstruction to include a robust model of temporal effects. The benefits include, no geometric distortion and high speed single shot simultaneous acquisition of field maps, M0, T2 and T2' measurements at reasonable resolutions. This is intended to be a short tutorial to get you rapidly up to speed on the technique. PARSE is a novel magnetic resonance imaging technique that uses an improved spin system model to extract far more information from the RF signal than traditional techniques. This site will be updated to show the latest information and news relating to the PARSE project. You can also download sample code and sample data from this code repository. The code is being developed at the Center for the Development of Functional Imaging at the University of Alabama at Birmingham and at Auburn University. The tools are currently written in Matlab.

What is on this site

PARSE is parameter assessment by retrieval from signal encoding. This guide assumes a familiarity with the basic theory of magnetic resonance imaging (MRI). The current algorithms are implemented in Matlab and some familiarity with this language might be helpful.

• the gallery pages contain an overview of the project and some nice pictures of results
• this wiki contains documentation, notes, and HowTos
• the subversion repository (under the "source" tab above)
• data is a directory containing sample data
• yase contains an example plcg implemtation
• doc contains documentaion for the code
• traj contains gradient waveform generation code
• vseq contains Varian UnityInova specific pulse sequence sample code
• cal contains sample matlab code to process calibration data to generate calibrated k-trajectories

Getting Started

The first thing to do is download example code and data. The preferred way to do this is via subversion (svn). Alternatively you can download the file first_parse.zip from the downloads section of this site. See UseTheSource for details on downloading the sample code.