Abstract #2948

MP-PCA image denoising technique for high resolution quantitative susceptibility mapping (QSM) of the human brain in vivo

Liad Doniza¹, Neta Stern², Dvir Radunsky², Coral Helft³, Patrick Fuchs⁴, Anita Karsa⁴, Karin Shmueli⁴, and Noam Ben-Eliezer^2,3,5

¹Department of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel, ²The Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel, ³Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel, ⁴Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ⁵Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States

Synopsis

Keywords: Data Processing, Susceptibility, Denoising

Quantitative susceptibility mapping (QSM) has many clinical applications such as distinguishing between acute and chronic multiple sclerosis (MS) lesions, and probing microbleeds in traumatic brain injury. High scan resolutions improve diagnostic quality and reduce partial volume artifacts albeit at a price of a lower signal-to-noise ratio (SNR). In this study, we introduce a principal component analysis (PCA) denoising algorithm for QSM data, showing the ability to generate QSM maps of the human brain at 0.6x0.6x0.6 mm³resolution at 3T in vivo.

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