Keywords: Body, Pediatric, LAVA-Flex, 3D FLEX
Motivation: Fat suppressed T1 images, such as LAVA-FLEX, are routinely used in pediatric abdominal imaging, but can suffer for SNR and IQ issues.
Goal(s): Our goal was to validate application of 3D deep learning to 3D LAVA-FLEX via image quality assessment and noise characterization.
Approach: DL and conventionally reconstructed images were assessed by two radiologists and noise characteristics were evaluated by calculation of total variation and number of detected edges.
Results: The radiologists preferred DL in a majority of cases (>80%), with noticeably lower noise and improved sharpness in DL images.
Impact: The application of DL to routine pediatric 3D LAVA-FLEX imaging provides enhanced diagnostic quality, and has the potential to improve pediatric patient care.
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