通过深度强化学习进行3D几何牙齿对齐规划

中文摘要 AI 辅助

3D几何牙齿对齐规划是现代数字正畸学的基石，它决定了从初始错牙合到最终目标对齐的连续轨迹。本文提出了一种新颖的深度强化学习（DRL）框架，以自动生成这些对齐路径。我们将规划过程制定为马尔可夫决策过程（MDP），以捕捉其顺序决策性质，专注于优化几何轨迹，同时整合诸如避免牙齿间碰撞和路径效率等基本空间约束。所提出的方法利用深度确定性策略梯度（DDPG）算法，并通过三项关键创新进行增强：（1）基于Transformer的智能体，用于对牙齿之间的复杂空间相互作用进行建模并管理高维状态-动作空间；（2）动态掩码方案，限制每一步仅对稀疏的牙齿子集进行移动，更好地反映顺序对齐的临床逻辑；（3）两阶段课程学习策略，逐渐增加任务难度以确保训练稳定性和高效路径发现。我们在基于临床数据的10K专家设计治疗计划数据集上评估了我们的方法。实验结果表明，我们的方法在路径安全性和几何效率方面优于现有基线，为3D几何正畸对齐规划提供了强大的自动化解决方案。

英文摘要

3D geometric tooth alignment planning, which determines sequential trajectories from initial malocclusion to the final target alignment, is a cornerstone of modern digital orthodontics. This paper presents a novel deep reinforcement learning (DRL) framework to automate the generation of these alignment paths. We formulate the planning process as a Markov Decision Process (MDP) to capture its sequential decision-making nature, focusing on optimizing geometric trajectories while integrating essential spatial constraints, such as inter-dental collision avoidance and path efficiency. The proposed method leverages the Deep Deterministic Policy Gradient (DDPG) algorithm, enhanced by three key innovations: (1) a Transformer-based agent to model complex spatial interactions between teeth and manage high-dimensional state-action spaces; (2) a dynamic masking scheme that restricts movement to a sparse subset of teeth per step, better reflecting the clinical logic of sequential alignment; and (3) a two-stage curriculum learning strategy that gradually increases task difficulty to ensure training stability and efficient path discovery. We evaluate our approach on a dataset of 10K expert-designed treatment plans based on clinical data. Experimental results demonstrate that our method outperforms existing baselines in terms of path safety and geometric efficiency, providing a robust and automated solution for 3D geometric orthodontic alignment planning.

发表机构

• School of Software Technology, Zhejiang University（浙江大学软件学院）
• State Key Laboratory of CAD&CG, Zhejiang University（浙江大学CAD&CG国家重点实验室）
• Stomatology Hospital, Zhejiang University School of Medicine（浙江大学医学院附属口腔医院）

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