Keywords: Machine Learning/Artificial Intelligence, Image ReconstructionMagnetic resonance imaging (MRI) is a useful tool to diagnose lumbar endplate inflammation. It is thus important to improve diagnostic accuracy by improving image quality. In this study, we compared signal-to-noise ratio (SNR), contrast noise ratio (CNR) and subjective scores between original images and deep learning reconstruction (DL Recon) images in 31 patients diagnosed with lumbar endplate inflammation. It was observed that the deep learning reconstructed images outperformed conventional images in terms of both subjective scores and objective values.
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