Automatic and Robust Skull Registration Based on Discrete Uniformization

Junli Zhao, Xin Qi, Chengfeng Wen, Na Lei, Xianfeng Gu; The IEEE International Conference on Computer Vision (ICCV), 2019, pp. 431-440

Abstract


Skull registration plays a fundamental role in forensic science and is crucial for craniofacial reconstruction. The complicated topology, lack of anatomical features, and low quality reconstructed mesh make skull registration challenging. In this work, we propose an automatic skull registration method based on the discrete uniformization theory, which can handle complicated topologies and is robust to low quality meshes. We apply dynamic Yamabe flow to realize discrete uniformization, which modifies the mesh combinatorial structure during the flow and conformally maps the multiply connected skull surface onto a planar disk with circular holes. The 3D surfaces can be registered by matching their planar images using harmonic maps. This method is rigorous with theoretic guarantee, automatic without user intervention, and robust to low mesh quality. Our experimental results demonstrate the efficiency and efficacy of the method.

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[bibtex]
@InProceedings{Zhao_2019_ICCV,
author = {Zhao, Junli and Qi, Xin and Wen, Chengfeng and Lei, Na and Gu, Xianfeng},
title = {Automatic and Robust Skull Registration Based on Discrete Uniformization},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}