Abstract #1374

Cardiac MR Denoising Inline Neural Network (CaDIN).

Siyeop Yoon¹, Salah Assana¹, Manuel A. Morales¹, Julia Cirillo¹, Patrick Pierce¹, Beth Goddu¹, Jennifer Rodriguez¹, and Reza Nezafat¹

¹Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Image ReconstructionThe diagnostic confidence in the interpretation of cardiac MR scans can be improved by enhancing the signal-to-noise ratio (SNR). Traditional image denoising has been studied extensively to improve SNR in cardiac MRI, but with limited success due to the resulting blurring. In this study, we sought to develop and evaluate cardiac MR denoising inline neural network (CaDIN) for improving SNR in cardiac MRI.

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