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Automatic and accurate dental arch segmentation is a fundamental task in computer-aided dentistry. Recent trends in digital dentistry are tackling the design of 3D crowns using artificial intelligence, which initially requires a proper semantic segmentation of teeth from intraoral scans (IOS). In practice, most IOS are partial with as few as three teeth on the scanned arch, and some of them might have preparations, missing, or incomplete teeth. Existing deep learning-based methods (e.g., MeshSegNet, DArch) were proposed for dental arch segmentation, but they are not as efficient for partial arches that include imperfections such as missing teeth and preparations. In this work, we present the ArchSeg framework that can leverage various deep learning models for semantic segmentation of perfect and imperfect dental arches. The Point Transformer V2 deep learning model is used as the backbone for the ArchSeg framework. We present experiments to demonstrate the efficiency of the proposed framework to segment arches with various types of imperfections. Using a raw dental arch scan with two labels indicating the range of present teeth in the arch (i.e., the first and the last teeth), our ArchSeg can segment a standalone dental arch or a pair of aligned master/antagonist arches with more available information (i.e., die mesh). Two generic models are trained for lower and upper arches; they achieve dice similarity coefficient scores of $0.936\pm 0.008$ and $0.948\pm 0.007$, respectively, on test sets composed of challenging imperfect arches. Our work also highlights the impact of appropriate data pre-processing and post-processing on the final segmentation performance. Our ablation study shows that the segmentation performance of the Point Transformer V2 model integrated in our framework is improved compared with the original standalone model. Full article

Removable functional appliances (RFA) have long been employed to address Class II malocclusion, particularly in cases involving a significant overjet, a deep bite, and molar class 2 issues. Notably divergent from RFA, myofunctional appliances (PMA) offer several distinct advantages, including applicability in noncompliant patients, adaptability in cases of dental element scarcity, suitability for allergic patients, impression-free utilization, and reduced costs. Within the array of clinical cases treated with PMA, we chose to present an intricate case involving an 8-year-old girl. Our aim was to showcase the immediate effects of PMA and to track the progress over a two-year span. Following one year of PMA treatment, substantial improvements were observed in a large overjet, a deep bite, and lip incompetence—factors often associated with elevated risks of dental trauma. These improvements not only positively impacted dental aesthetics but also engendered normalized nasal respiration and diminished palatal impingement, thereby enhancing the overall quality of life. Upon reaching the two-year mark, the clinical status pertaining to Class II malocclusion remained stable. Further treatment was advised in a subsequent phase to refine imperfections in the dental arch form. Nonetheless, comprehensive data from the prolonged follow-up of patients treated with these appliances are essential to establish robust scientific evidence concerning their long-term efficacy. Full article