Abstract #2842

Rapid Zero-shot Image Denoising for Quantitative Imaging on a Point-Of-Care 46-mT-MRI System

Yiming Dong¹, Beatrice Lena¹, Tom O’Reilly¹, Mathieu Mach¹, Chinmay Rao², Ziyu Li³, Matthias J.P. van Osch¹, Andrew Webb¹, and Peter Börnert^1,4

¹C.J. Gorter MRI Center, Department of Radiology, LUMC, Leiden, Netherlands, ²Division of Image Processing, Department of Radiology, LUMC, Leiden, Netherlands, ³Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ⁴Philips Research Hamburg, Hamburg, Germany

Synopsis

Keywords: Low-Field MRI, Low-Field MRI, denoising

Motivation: Low-field MRI holds the promise of expanding access to healthcare. The low signal-to-noise ratio (SNR) poses a significant challenge to acquiring diagnostically useful information in a reasonable scanning time.

Goal(s): To overcome the challenge of low SNR in low-field MRI, achieving fast, self-supervised denoising.

Approach: A rapid 4D-denoising method utilizing the Zero-Shot-Noise2Noise framework is proposed, without the need for intensive network training.

Results: This method provides fast denoising in just 10-20 seconds per case and significantly boosts SNR efficiency, reducing the number of measrued TIs and TEs needed for precise, high-quality T₁/T₂ mapping.

Impact: This study's fast 4D-denoising approach revolutionizes low-field MRI by enhancing SNR without extensive training datasets, enabling faster, more efficient imaging and broadening diagnostic accessibility in resource-limited settings.

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