K-U-KAN reconstructs 3D dental models from single X-rays

Researchers have developed K-U-KAN, a novel three-stage pipeline for reconstructing 3D dental models from single panoramic X-ray images. This method utilizes Kolmogorov-Arnold Networks (U-KAN) enhanced with Koopman operator theory to efficiently recover depth information, outperforming existing neural representations in training speed and robustness. K-U-KAN achieves comparable signal and structure metrics to transformer and implicit baselines while offering improved perceptual quality and interpretability, making it a more practical tool for clinical dental pipelines. AI

影响 Introduces a more efficient and robust method for 3D dental reconstruction from single X-rays, potentially improving clinical workflows.

排序理由 The cluster contains an academic paper detailing a new method for 3D dental reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

• Bikram Keshari Parida
• Kolmogorov-Arnold Networks
• Koopman operator theory
• K-U-KAN

• 论文
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