Meeting Banner
Abstract #5195

Improving the Noise Propagation Behavior of Different Fatty Acid Quantification Techniques using Spectral Denoising

Manuel Schneider1, Felix Lugauer1, Dominik Nickel2, Brian M Dale3, Berthold Kiefer2, Andreas Maier1, and Mustafa R Bashir4,5

1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 2MR Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, 3MR R&D Collaborations, Siemens Healthcare, Cary, NC, United States, 4Radiology, Duke University Medical Center, Durham, NC, United States, 5Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC, United States

MRI is not only capable of quantifying the fat content, but also the fatty acid composition of human adipose tissue. Especially for low fat fractions, fatty acid quantification is sensitive to image noise. Including prior information or additional parameter approximations into the quantification method helped to improve the noise propagation behavior, but also introduced a systematic bias. Performing spectral denoising in between image reconstruction and fatty acid quantification kept the systematic bias as well as the noise in the parameter maps low, and hence allows for more flexible protocol selection and shorter acquisition times.

This abstract and the presentation materials are available to members only; a login is required.

Join Here