https://www.selleckchem.com/products/ms-275.html
Cephalometric analysis is a fundamental examination which is widely used in orthodontic diagnosis and treatment planning. Its key step is to detect the anatomical landmarks in lateral cephalograms, which is time-consuming in traditional manual way. To solve this problem, we propose a novel approach with a cascaded three-stage convolutional neural networks to predict cephalometric landmarks automatically. In the first stage, high-level features of the craniofacial structures are extracted to locate the lateral face area which helps to ove
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