Video from ISMRM 2019: Jong Chul Ye on machine learning and data reconstruction

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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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(A) Ultrafast MR image obtained 14 seconds after aortic enhancement shows 0.4-cm focus (arrow) in the left breast at 3-o’clock position, 4.5 cm from index cancer (not shown). (B) Ultrafast MR image obtained 23 seconds after aortic enhancement shows wash-in (arrow) of background parenchymal enhancement (BPE). (C) and (D) On first standard postcontrast subtraction MR images, focus (arrow, C) and BPE (arrow, D) are indistinguishable. MRI-guided biopsy of focus yielded grade 2 invasive lobular carcinoma. Image courtesy of the ARRS.
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