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Abstract #2413

Optimization of Fat-Water Separation Algorithm Selection and Options Using Image-Based Metrics with Validation by ISMRM Fat-Water Challenge Datasets

David S. Smith1, Johan Berglund2, Joel Kullberg3, Hkan Ahlstrm3, Malcolm J. Avison4, E. Brian Welch5

1Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States; 2Philips Healthcare, Stockholm, Sweden; 3Department of Radiology, Uppsala University, Uppsala, Sweden; 4Department of Pharmacology, Vanderbilt University, Nashville, TN, United States; 5Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States

This research describes a robust fat-water separation algorithm for multi-echo MRI applicable to datasets spanning a wide range of anatomy, magnetic field strengths and collected echo times. The algorithm is validated in the context of the 2012 ISMRM Fat-Water Challenge. We show evidence of the power of image-based metrics to predict the best (or nearly best) option among multiple results obtained with various advanced fat-water separation algorithms. No matter the contest outcome, we look forward to sharing the full details of our final algorithm and to seeing many excellent solutions developed by other teams participating in the ISMRM Fat-Water Challenge.

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Keywords

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