Explore the clinical evidence supporting the effectiveness and impact of the Relu® Engine AI models.
Deep convolutional neural network-based automated segmentation and classification of teeth with orthodontic brackets on cone-beam computed-tomographic images: a validation study
Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.
Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images – A validation study.
Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT
A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation study
Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography
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