Construction of Analysis-Suitable Vascular Models Using Axis-Aligned Polycubes.

Area of Science:

• Biomedical research
• Medical imaging
• Computational modeling

Background:

• Image-based modeling uses medical imaging for patient-specific physiological simulations.
• Cardiovascular structure segmentation creates surface meshes, but analytic representations are often needed for manipulation and advanced analysis.
• Converting discrete surface models to analysis-suitable formats, especially for complex vascular geometries, is challenging.

Purpose of the Study:

• To present a framework for converting discrete surface models of vascular geometries into analysis-suitable NURBS representations.
• To enable easier manipulation and integration of patient-specific models for applications like medical device design and surgical planning.
• To facilitate the use of advanced computational methods like isogeometric analysis (IGA).

Main Methods:

• Developing a framework to convert discrete surface models of vascular geometries into NURBS.
• Decomposing vascular geometry into a polycube structure.
• Forming a globally valid parameterization from the polycube structure.

Main Results:

• Successfully converted discrete surface models of vascular geometries into analysis-suitable NURBS representations.
• Demonstrated the accuracy and fidelity of the NURBS parameterization compared to the original geometry.
• Provided practical examples showcasing the framework's utility.

Conclusions:

• The proposed framework effectively addresses the challenge of converting discrete vascular models to analysis-suitable NURBS.
• This method enhances the capabilities of image-based modeling for cardiovascular research and clinical applications.
• The approach supports advanced computational analyses and patient-specific simulations.