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Acquisition of point cloud in CT image space to improve accuracy of surface registration: Application to neurosurgical navigation system

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Abstract

One important technique of surgical navigation is surface registration that matches coordinates in two different spaces. We proposed a novel method to extract an optimal point cloud in image space corresponding to the point cloud in patient space to improve the registration accuracy. In the hemispherical study, our proposed method demonstrated a reduced surface registration error (SRE) and target registration error (TRE) compared to the conventional method in all cases (number of points, distribution, noise). In the phantom study, the SRE and TRE were low and stable in the proposed method, with SRE reduced by 22 % and TRE by 18 % (p < 0.05). The proposed method was not affected by the number of points, distribution, or noise in the point cloud, and it could improve the registration accuracy without the aid of additional equipment.

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Abbreviations

R :

Rotation matrix

T :

Translation matrix

s:

Point cloud in the patient space

c:

Point cloud in the image space

a :

Weighting factor

P* :

Projected point

P :

Projecting point

t :

Projection distance

np :

Projection vector

c :

Sum of weighting factor

r :

Radial distance

θ:

Polar angled

φ:

Azimuthal angle

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP; No. NRF-2016R1A2B3009013).

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Author notes

  1. These authors equally contributed to this work as first author.

Authors and Affiliations

  1. Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066 Seoburo, Jangan, Suwon, Gyeonggi, 16419, Korea

    Hakje Yoo, Ahnryul Choi & Joung Hwan Mun

  2. Department of Biomedical Engineering, College of Medical Convergence, Catholic Kwandong University, 24 Beomilro 579 beon-gil, Gangneung, Gangwon, 25601, Korea

    Ahnryul Choi

Authors
  1. Hakje Yoo
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Correspondence to Joung Hwan Mun.

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Recommended by Editor Sehyun Shin

Hakje Yoo received his B.S. degree in biomechatronics engineering from Sung-kyunkwan University. He is now a Ph.D. student in the Biomechatronics Engineering at Sungkyunkwan University. His research interests include biomedical engineering and sports biomechanics and surgical navigation system.

Ahnryul Choi is an Assistant Professor of the Department of Biomedical Engineering at Catholic Kwandong University. He received his Ph.D. degree in Biome-chatronic Engineering from Sungkyunk-wan University. His research interests include the development of medical device and expert system based on machine learning techniques.

Joung Hwan Mun received a Ph.D. degree in Biomedical Engineering from The University of Iowa, USA. Currently he is a Professor of Department of Bio-mechatronic Engineering at Sungkyunk-wan University. His research interests include 3D human modelling, musculoskeletal injuries, sports medicine, ergonomics, bio-medical electronics and expert system based on artificial intelligence.

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Yoo, H., Choi, A. & Mun, J.H. Acquisition of point cloud in CT image space to improve accuracy of surface registration: Application to neurosurgical navigation system. J Mech Sci Technol 34, 2667–2677 (2020). https://doi.org/10.1007/s12206-020-0540-6

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  • DOI: https://doi.org/10.1007/s12206-020-0540-6

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