CHaRM is an end-to-end deep learning method that conditions heatmap-based landmark localization on predicted tooth presence, achieving 0.56 mm error on standard dentitions and up to 14.8x faster inference than two-stage baselines.
Automatic tooth segmentation and dense correspondence of 3d dental model
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CHaRM: Conditioned Heatmap Regression Methodology for Accurate and Fast Dental Landmark Localization
CHaRM is an end-to-end deep learning method that conditions heatmap-based landmark localization on predicted tooth presence, achieving 0.56 mm error on standard dentitions and up to 14.8x faster inference than two-stage baselines.