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Deep learning super-resolution for dental CBCT using micro-CT reference and edge loss function
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DOI：10.1016/j.jdent.2025.106209.png)
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Abstract
En 中文
Cone-beam computed tomography (CBCT) is used extensively in dental practice but has limited spatial resolution for visualising fine root canal structures. Micro-computed tomography (micro-CT) offers superior resolution but is unsuitable for clinical use. This study investigated the possibility of enhancing CBCT resolution through deep learning-based super-resolution, using paired micro-CT images as the ground truth.
Keywords:
CBCT
deep learning
edge-loss
micro-CT
super-resolution
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