Video from ISMRM 2019: Tal Arbel on machine learning and image analysis

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Figure: Improved image quality with a generative adversarial network architecture for low- to high-field-strength image translation, called LowGAN. (A–C) Top: High-field-strength (3-T) and low-field-strength (64-mT) images and LowGAN outputs for a single participant across (A) fluid-attenuated inversion recovery (FLAIR), (B) T1-weighted (T1w), and (C) T2-weighted (T2w) contrasts. Bottom: Graphs demonstrate the structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and feature similarity index (FSIM) between high field strength and low field strength (64-mT) and high field strength and LowGAN outputs. a.u. = arbitrary units.****p ≤ 0.0001. Images and caption courtesy of Radiology and the RSNA.
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