"深度学习框架实现多模态融合重建牙齿骨骼的方案与应用"

Deep learning has revolutionized the field of medical imaging, particularly in the domain of dental reconstruction and recognition. In a recent article titled "Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction", the authors proposed a novel approach to tooth-bone reconstruction using a combination of cone-beam CT (CBCT) and intraoral mesh scans (IOS). The study highlighted the importance of accurately identifying and segmenting CBCT and IOS images in order to create a precise 3D tooth-bone reconstruction. By developing a deep multimodal fusion pipeline, the researchers were able to integrate both modalities and achieve a higher level of accuracy in their reconstructions. The authors also introduced new techniques for segmenting CBCT and IOS images, as well as for merging 3D meshes to create a comprehensive reconstruction. They collected a multimodal dataset to validate their methods and demonstrated the real-world applicability of their approach. Overall, this research represents a significant advancement in the field of dental imaging and reconstruction, showcasing the potential of deep learning frameworks for enhancing clinical applications in dentistry. By leveraging the power of deep learning, researchers are able to improve the accuracy and efficiency of tooth-bone reconstructions, ultimately leading to better patient outcomes and more effective dental treatments.