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基于背景的个体化容积模型用于患者特异性手术模拟:一种无需分割、无需建模的框架。

Background-incorporated volumetric model for patient-specific surgical simulation: a segmentation-free, modeling-free framework.

机构信息

Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.

出版信息

Int J Comput Assist Radiol Surg. 2011 Jan;6(1):35-45. doi: 10.1007/s11548-010-0456-1. Epub 2010 May 8.

Abstract

PURPOSE

Patient-specific surgical simulation imposes both practical and technical challenges. We propose a segmentation-free, modeling-free framework that creates medical volumetric models for intuitive volume deformation and manipulation in patient-specific surgical simulation.

METHODS

The proposed framework creates a volumetric model based upon a new form of mesh structure, a Volume Proxy Mesh (VPM). The model can be generated in two phases: the vertex placement phase and mesh improvement phase. Vertices of a VPM are assigned to an initial location by curvature-based vertex placement method, and followed by mesh improvement performed by Particle Swarm Optimization (PSO).

RESULTS

The framework is applied to several kidney CT volume data. Using the framework, the resulting models are closely tailored to the detailed features of the datasets. Moreover, the resulting VPM meshes can support broader spectrum deformation between the manipulated organ and its surrounding tissues. Progress in the mesh quality of the final mesh also shows that PSO is feasible for mesh improvement.

CONCLUSION

The framework was applied to several kidney CT volume datasets. Using the framework, the resulting models are closely tailored to the detailed features of the datasets. Moreover, the resulting VPM meshes can support broader spectrum deformation between the manipulated organ and its surrounding tissues. Evaluation of final mesh quality shows that PSO is feasible for mesh improvement.

摘要

目的

患者特定的手术模拟带来了实际和技术上的挑战。我们提出了一种无分割、无模型的框架,为患者特定的手术模拟创建了用于直观体积变形和操作的医学体积模型。

方法

所提出的框架基于一种新的网格结构,即体积代理网格(VPM),创建了一个体积模型。该模型可以分两个阶段生成:顶点放置阶段和网格改进阶段。VPM 的顶点通过基于曲率的顶点放置方法被分配到初始位置,然后通过粒子群优化(PSO)进行网格改进。

结果

该框架应用于几个肾脏 CT 体数据集。使用该框架,生成的模型紧密贴合数据集的详细特征。此外,生成的 VPM 网格可以支持操作器官与其周围组织之间更广泛的变形谱。最终网格的网格质量的改进也表明 PSO 对于网格改进是可行的。

结论

该框架应用于几个肾脏 CT 体数据集。使用该框架,生成的模型紧密贴合数据集的详细特征。此外,生成的 VPM 网格可以支持操作器官与其周围组织之间更广泛的变形谱。最终网格质量的评估表明 PSO 对于网格改进是可行的。

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