通过通过神经SDF和辐射场进行颜色感知反向染来增强内镜场景重建
Zhibao Qin1, Qi Chen1, Kai Qian2
1Yunnan Key Laboratory of Opto-electronic Information Technology, Yunnan Normal University, Kunming 650500, China.
Biomedical optics express
|June 13, 2024
概括
这项研究介绍了Endoscope-NeSRF,这是一个新的网络,用于从内镜图像创建现实的3D器官模型. 它通过改善形状和颜色重建来增强虚拟外科训练,以更好地进行外科模拟.
科学领域:
- 医疗成像医学成像
- 计算机图形 计算机图形
- 手术模拟器手术模拟器
背景情况:
- 虚拟手术培训需要现实的3D器官模型.
- 目前的方法难以从医疗图像中准确地进行颜色和几何重建.
- 内镜成像缺乏详细的外观信息.
研究的目的:
- 开发一个新的网络,内镜-NeSRF,用于从内镜图像同时进行器官的几何和外观重建.
- 提高虚拟外科培训环境的现实性.
- 克服传统重建方法的局限性.
主要方法:
- 利用神经辐射场和信号距离函数 (SDF) 来进行器官模型重建.
- 包含光对象相互作用的先前知识和扩展的面罩,用于边缘精细化.
- 开发了一种突出适应性优化策略,以消除反射.
- 采用反向染和双向反射分布函数 (BRDF) 染用于实时可视化.
主要成果:
- 内镜-NeSRF实现了与即时-NGP相似的外观重建.
- 与最先进的方法相比,表现出更高的几何重建精度.
- 从多视图内镜图像生成了具有现实的外观的详细几何模型.
- 成功删除了亮点文物,防止了白色效应.
结论:
- 内镜-NeSRF在为虚拟手术模拟创建现实的3D器官模型方面取得了重大进展.
- 该方法增强了对有效的医疗培训至关重要的视觉真实性.
- 提供了比传统的重建技术更准确和视觉丰富的替代方案.
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