融合口内扫描与CBCT数据，重建高保真3D牙齿模型
High-Fidelity 3D Tooth Reconstruction by Fusing Intraoral Scans and CBCT Data via a Deep Implicit Representation
- 用深度隐式表示融合口内扫描冠部和CBCT根部数据
- 生成无接缝、闭合且解剖结构一致的3D牙齿模型
- 适合临床数字化牙科与种植规划应用
高保真3D牙齿模型对数字牙科至关重要，需同时精确还原牙冠细节与完整牙根形态。临床影像存在局限：锥形束计算机断层扫描（CBCT）可捕捉牙根但牙冠噪声大、分辨率低；口内扫描（IOS）提供高保真牙冠但无法获取牙根信息。简单拼接导致不自然接缝与伪影。本文提出一种全自动化融合流程，利用深度隐式表示融合CBCT与IOS数据。方法首先分割并稳健配准牙齿实例，构建结合IOS牙冠与CBCT牙根的混合代理网格；核心是使用该噪声代理引导特定类别的DeepSDF网络优化，将输入投影至理想牙齿形状的已学习流形，生成无缝、闭合且解剖一致的模型。定性与定量评估表明，本方法成功保留了来自IOS的高保真牙冠和来自CBCT的患者特异性牙根形态，克服了单一模态及简单拼接的局限。
原文摘要 · Abstract (English)
High-fidelity 3D tooth models are essential for digital dentistry, but must capture both the detailed crown and the complete root. Clinical imaging modalities are limited: Cone-Beam Computed Tomography (CBCT) captures the root but has a noisy, low-resolution crown, while Intraoral Scanners (IOS) provide a high-fidelity crown but no root information. A naive fusion of these sources results in unnatural seams and artifacts. We propose a novel, fully-automated pipeline that fuses CBCT and IOS data using a deep implicit representation. Our method first segments and robustly registers the tooth instances, then creates a hybrid proxy mesh combining the IOS crown and the CBCT root. The core of our approach is to use this noisy proxy to guide a class-specific DeepSDF network. This optimization process projects the input onto a learned manifold of ideal tooth shapes, generating a seamless, watertight, and anatomically coherent model. Qualitative and quantitative evaluations show our method uniquely preserves both the high-fidelity crown from IOS and the patient-specific root morphology from CBCT, overcoming the limitations of each modality and naive stitching.
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