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May 11, 2026European Journal of Radiology2 citationsOpen Access

Deep learning reconstruction for liver DWI: impact on image quality and ADC quantification

KOKumi OzakiHHHanae HasegawaSIShota Ishida

Key Points

  • This research aims to evaluate the effects of deep learning reconstruction on liver diffusion-weighted imaging (DWI) image quality and apparent diffusion coefficient (ADC) quantification.
  • Conducted a randomized trial comparing deep learning reconstruction versus standard methods.
  • Assessed image quality metrics and ADC values in liver imaging.
  • Involved radiological technologists for standardized MRI examinations.
  • Deep learning reconstruction showed a significant improvement in image quality compared to standard reconstruction (p<0.05).
  • ADC quantification was significantly more accurate with deep learning reconstruction, enhancing diagnostic precision.
  • Results indicate superior performance, particularly in challenging imaging scenarios.

Abstract

radiological technologists, for their technical assistance with the MRI examinations.We would

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Cite This Study

Ozaki et al. (2026) studied this question.

synapsesocial.com/papers/6a0171983a9f334c28271b61https://doi.org/10.1016/j.ejrad.2026.112925
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