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Abstract #5133

Maximal Contrasts Using MR Complex Data: With an Application to Visualise Cortical Structure

Zhaolin Chen1, Leigh A. Johnston2, Gary F. Egan3

1Florey Neuroscience Institutes, Carlton, VIC, Australia; 2Electrical and Electronic Engineering, University of Melbourne; 3Centre for Neuroscience, University of Melbourne


Recent developments in MR phase imaging enable analyses of MR signals in the complex domain. However, in clinical diagnoses and anatomical studies, it is necessary to objectively map complex MR signals to a one-dimensional signal for visualisation. The Susceptibility Weighted Imaging (SWI) method uses the phase image to calculate a phase mask that is multiplied with the magnitude image to enhance the contrast caused by tissue susceptibility. SWI has demonstrated great advantage in contrast enhancement for various applications. In this work, we introduce a new method called Maximum Contrast Image (MCI) to further improve the image contrast from complex MR signals. Enhanced image contrasts obtained with the new method have been demonstrated using a 3T dataset of a cortical brain section. Furthermore, in contrast to the nonlinear operation in SWI, the MCI method uses a linear operation, which permits meaningful quantification of the MCI signals.