Abstract #4964

Constrained Reconstruction of White Noise (CROWN) for Strategically Acquired Gradient Echo (STAGE) Imaging

Paul Kokeny¹, Qiuyun Xu¹, Sara Gharabaghi¹, Sean Sethi^1,2, Yu Liu³, Youmin Zhang³, Peng Liu³, Naying He³, Fuhua Yan³, and E. Mark Haacke^1,2,4

¹SpinTech MRI, Bingham Farms, MI, United States, ²Radiology, Wayne State University, Detroit, MI, United States, ³Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, Shanghai, China, ⁴Neurology, Wayne State University, Detroit, MI, United States

Synopsis

Keywords: Image Reconstruction, Quantitative ImagingBy using the inherent relationship between proton spin density (PSD) and T1, we propose a new image-processing approach to reduce noise called CROWN (Constrained Reconstruction of White Noise). Firstly, we established a linear relationship between these two parameters, then applied a cost function to constrain simulated Strategically Acquired Gradient Echo (STAGE) PSD map and T1 map data in the presence of noise. Secondly, we applied this approach to in vivo STAGE images to reduce noise and improve SNR without the loss of image detail. CROWN has the potential to make higher resolution or faster imaging viable with improved SNR.

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