Keywords: Diffusion Reconstruction, Liver, deep learning reconstructed Diffusion Weighted Imaging
Motivation: Deep learning (DL) reconstructions can improve image quality and/or reduce acquisition time in diffusion-weighted imaging (DWI).
Goal(s): This study aims to assess, quantitatively and qualitatively, DL-accelerated DWI in 50 patients with colorectal cancer undergoing liver examinations.
Approach: Three DWI series are compared: a moderately-accelerated DL-DWI, a corresponding standard reconstruction and a highly-accelerated DL-DWI.
Results: The moderately-accelerated DL reconstruction method provides better image quality than a standard reconstruction. Its ADC estimates in liver, spleen and liver metastases are slightly higher than ADC estimates from the standard reconstruction.
Impact: This study evaluated DL-accelerated DWI in 50 patients undergoing liver examinations by comparing three DWI series. The moderately-accelerated acquisition with DL reconstruction provided better image quality versus the standard reconstruction; its ADC was slightly higher than the standard-based ADC.
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