Robust Spectral Denoising for Water-Fat Separation in Magnetic Resonance Imaging

Lugauer F, Nickel D, Wetzl J, Kannengiesser SAR, Maier A, Hornegger J (2015)

Publication Status: Published

Publication Type: Conference contribution

Publication year: 2015

Journal

Publisher: Springer-verlag

Book Volume: 9350

Pages Range: 667-674

Conference Proceedings Title: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II

DOI: 10.1007/978-3-319-24571-3_80

Abstract

Fat quantification based on the multi-echo Dixon method is gaining importance in clinical practice as it can match the accuracy of spectroscopy but provides high spatial resolution. Accurate quantification protocols, though, are limited to low SNR and suffer from a high noise bias. As the clinically relevant water and fat components are estimated by fitting a non-linear signal model to the data, the uncertainty is further amplified. In this work, we first establish the low-rank property and its locality assumptions for water-fat MRI and, consequently, propose a model-consistent but adaptive spectral denoising. A robust noise estimation in combination with a risk-minimizing threshold adds to a fully-automatic method. We demonstrate its capabilities on abdominal fat quantification data from in-vivo experiments. The denoising reduces the fit error on average by 37% and the uncertainty of the fat fraction by 58% in comparison to the original data while being edge-preserving.

Authors with CRIS profile

Involved external institutions

Siemens AG, Healthcare Sector Germany (DE)

How to cite

APA:

Lugauer, F., Nickel, D., Wetzl, J., Kannengiesser, S.A.R., Maier, A., & Hornegger, J. (2015). Robust Spectral Denoising for Water-Fat Separation in Magnetic Resonance Imaging. In 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II (pp. 667-674). Springer-verlag.

MLA:

Lugauer, Felix, et al. "Robust Spectral Denoising for Water-Fat Separation in Magnetic Resonance Imaging." Proceedings of the 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II Springer-verlag, 2015. 667-674.

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