用手机视频实现伤口三维精准测量，提升临床评估效率与准确性。
Wound3DAssist: A Practical Framework for 3D Wound Assessment
- 基于单目手机视频构建3D伤口模型，自动完成重建与分割。
- 毫米级精度，20分钟内完成全流程评估，支持深度与组织分类。
- 适用于复杂曲面伤口，适合临床医生日常使用。
慢性伤口管理仍是重大医疗挑战，传统临床评估依赖主观且耗时的手动记录。尽管二维数字视频测量有所助益，但存在视角畸变、视野受限及无法捕捉深度等问题，尤其在解剖结构复杂或弯曲区域表现不佳。为此，我们提出Wound3DAssist——一种基于单目消费级视频的实用3D伤口评估框架。该框架通过短时手持智能手机视频生成高精度3D模型，实现非接触式、自动化的测量，视图无关且对相机运动鲁棒。系统集成3D重建、伤口分割、组织分类与周围区域分析，形成模块化流程。我们在具有已知几何结构的数字模型、硅胶模拟物和真实患者中评估该框架。结果表明，其可实现高质量伤口床可视化，达到毫米级精度，并提供可靠的组织成分分析。全流程评估耗时不足20分钟，证明其具备临床实际应用可行性。
原文摘要 · Abstract (English)
Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documentation methods. Although 2D digital videometry frameworks aided the measurement process, these approaches struggle with perspective distortion, a limited field of view, and an inability to capture wound depth, especially in anatomically complex or curved regions. To overcome these limitations, we present Wound3DAssist, a practical framework for 3D wound assessment using monocular consumer-grade videos. Our framework generates accurate 3D models from short handheld smartphone video recordings, enabling non-contact, automatic measurements that are view-independent and robust to camera motion. We integrate 3D reconstruction, wound segmentation, tissue classification, and periwound analysis into a modular workflow. We evaluate Wound3DAssist across digital models with known geometry, silicone phantoms, and real patients. Results show that the framework supports high-quality wound bed visualization, millimeter-level accuracy, and reliable tissue composition analysis. Full assessments are completed in under 20 minutes, demonstrating feasibility for real-world clinical use.
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