Watertight 2-manifold 3D bone surface model reconstruction from CT images based on visual hyper-spherical mapping

Tianran Yuan; Hongsheng Zhang; Hao Liu; Juan Du; Huiming Yu; Yimin Wang; Yabin Xu; Tianran Yuan; Hongsheng Zhang; Hao Liu; Juan Du; Huiming Yu; Yimin Wang; Yabin Xu

doi:10.3934/mbe.2021068

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 2: 1280-1313. doi: 10.3934/mbe.2021068

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Watertight 2-manifold 3D bone surface model reconstruction from CT images based on visual hyper-spherical mapping

1.
School of Mechanical and Material Engineering, Huaiyin Institute of Technology, Huaian, Jiangsu 223003, China
2.
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
3.
School of Medical Technology, Jiangsu College of Nursing, Huaian, Jiangsu 223005, China
4.
Department of Oral and Maxillofacial Surgery, Huaian First People's Hospital, Huaian, Jiangsu 223300, China

Received: 25 November 2020 Accepted: 05 January 2021 Published: 18 January 2021

This paper proposes a general algorithm to reconstruct watertight 2-manifold 3D bone surface model from CT images based on visual hyper-spherical mapping. The reconstruction algorithm includes three main steps: two-step thresholding, initial watertight surface reconstruction and shape optimization. Firstly, volume sampling points of the target bone with given narrower threshold range are extracted by thresholding with combination of 3D morphology operation. Secondly, visible points near the bone's outer surface are extracted from its corresponding volume sampling points by hyper-spherical projection mapping method. Thirdly, implicit surface reconstruction algorithm is employed on the extracted visible surface points to obtain an initial watertight 3D bone surface model which is used as the deformation model in the following accurate bone surface model generation stage. Finally, the initial surface model is deformed according to the segmentation data with wider threshold range under given constraints in order to achieve an accurate watertight 3D bone surface model. Experiment and comparison results show that the proposed algorithm can reconstruct watertight 3D bone surface model from CT images, and local details of the bone surface can be restored accurately for the cases used in this paper.
- bone surface reconstruction,
- CT image resampling and segmentation,
- surface deformation,
- visible points extraction
Citation: Tianran Yuan, Hongsheng Zhang, Hao Liu, Juan Du, Huiming Yu, Yimin Wang, Yabin Xu. Watertight 2-manifold 3D bone surface model reconstruction from CT images based on visual hyper-spherical mapping[J]. Mathematical Biosciences and Engineering, 2021, 18(2): 1280-1313. doi: 10.3934/mbe.2021068

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Abstract

This paper proposes a general algorithm to reconstruct watertight 2-manifold 3D bone surface model from CT images based on visual hyper-spherical mapping. The reconstruction algorithm includes three main steps: two-step thresholding, initial watertight surface reconstruction and shape optimization. Firstly, volume sampling points of the target bone with given narrower threshold range are extracted by thresholding with combination of 3D morphology operation. Secondly, visible points near the bone's outer surface are extracted from its corresponding volume sampling points by hyper-spherical projection mapping method. Thirdly, implicit surface reconstruction algorithm is employed on the extracted visible surface points to obtain an initial watertight 3D bone surface model which is used as the deformation model in the following accurate bone surface model generation stage. Finally, the initial surface model is deformed according to the segmentation data with wider threshold range under given constraints in order to achieve an accurate watertight 3D bone surface model. Experiment and comparison results show that the proposed algorithm can reconstruct watertight 3D bone surface model from CT images, and local details of the bone surface can be restored accurately for the cases used in this paper.

References

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