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

• Published in: International journal for computer assisted radiology and surgery Vol. 6; no. 1; pp. 35 - 45
• Main Authors: Hung, Kei Wai Cecilia, Nakao, Megumi, Yoshimura, Koji, Minato, Kotaro
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01-01-2011
• Subjects: Algorithms; Computer Imaging; Computer Science; Computer Simulation; Health Informatics; Humans; Imaging; Imaging, Three-Dimensional - methods; Medicine; Medicine & Public Health; Models, Theoretical; Original Article; Pattern Recognition and Graphics; Radiology; Surgery; Surgical Procedures, Operative; Vision; Patient-specific surgical simulation; Volumetric models; Segmentation-free; Curvature; Direct volume manipulation; Tetrahedral mesh improvement
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-010-0456-1

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.