APCReg：基于解剖先验的、经多视图投影与可靠性控制残差校正的CBCT与口腔内扫描（IOS）粗到精配准方法
APCReg: Anatomical-Prior-Guided Coarse-to-Fine CBCT--IOS Registration via Multi-View Projection and Reliability-Controlled Residual Correction
- Hangzhou Dianzi University（杭州电子科技大学）
- Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属第九人民医院）
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine（浙江大学医学院附属邵逸夫医院）
- Shanghai Stomatological Hospital & School of Stomatology, Fudan University（复旦大学附属口腔医院·口腔医学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对CBCT与IOS自动配准不可靠的问题，提出APCReg框架，通过多视图解剖粗配准、重叠感知残差配准及牙弓结构假设选择等技术，在60个颌骨对的评估中多项指标优于开源基线。
AI中文摘要：
锥束计算机断层扫描（CBCT）与口腔内扫描（IOS）的配准对患者特异性手术规划至关重要，但不同成像模态、有限重叠区域及大位姿偏移导致自动配准不可靠，临床配准仍依赖传统几何流程与医生手动调整。为解决这些挑战，本文提出APCReg，一种基于解剖先验的用于全局配准与可靠性控制残差校正的粗到精框架。具体而言，多视图解剖粗配准（MACR）执行有序正交投影对齐（颊侧、近中、咬合面），以在三维细化前分解六自由度搜索；重叠感知残差配准（OARR）结合共享KPConv特征、折叠牙弓长度提示、重叠门控交叉注意力及Sinkhorn匹配；最后，牙弓结构假设选择在保留的可靠对应关系上评估不同位姿，而无真值的粗保留机制条件性保留几何上可靠的粗位姿。在60个保留的颌骨对上，按该评估协议，APCReg实现亚毫米级的平均Chamfer距离0.87 mm、Hausdorff距离2.92 mm，且在评估的开源基线中，其在报告的六项指标里排名第一。
英文摘要：
Registration between cone-beam computed tomography (CBCT) and intraoral scans (IOS) is essential for patient-specific surgical planning. However, disparate imaging modalities, limited overlap, and large pose offsets make automated registration unreliable. Consequently, clinical registration remains dependent on conventional geometry pipelines and manual clinician adjustment. To address these challenges, we propose APCReg, an anatomical-prior-guided coarse-to-fine framework for global registration and reliability-controlled residual correction. Specifically, multi-view anatomical coarse registration (MACR) performs ordered orthogonal projection alignment (buccal, proximal, and occlusal) to decompose the six-degree-of-freedom search before three-dimensional refinement. Overlap-aware residual registration (OARR) combines shared KPConv features, a folded arch-length cue, overlap-gated cross-attention, and Sinkhorn matching. Finally, dental-arch-structured hypothesis selection evaluates diverse poses on held-out reliable correspondences, while a ground-truth-free coarse-retention guard conditionally retains a geometrically reliable coarse pose. On 60 held-out jaw pairs, APCReg achieves a submillimeter mean Chamfer distance of 0.87 mm and a Hausdorff distance of 2.92 mm under this evaluation protocol, and ranks first across the six reported metrics among the evaluated open-source baselines.
