Publications by authors named "Qizhi Qu"
Background: Although cone beam computed tomography (CBCT) plays an important role in the diagnosis and treatment of oral diseases, its image segmentation method needs to be further improved, and there are still objections about the clinical application effect of general anesthesia (GA) on children's dental fear (CDF).
Objective: This study aimed to investigate the application value of CBCT based on intelligent computer segmentation model in oral diagnosis and treatment of children in the context of biomedical signals, and to analyze the alleviating effect of GA on CDF.
Methods: Based on the regional level set (CV) algorithm, the local binary fitting (LBF) model was introduced to optimize it, and the tooth CBCT image segmentation model CV-LBF was established to compare the segmentation accuracy (SA), maximum symmetric surface distance (MSSD), average symmetric surface distance (ASSD), over segmentation rate (OR), and under segmentation rate (UR) between these model and other algorithms.