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Optimization Model for the Distribution of Fiducial Markers in Liver Intervention.

The distribution of fiducial markers is one of the main factors affected the accuracy of optical navigation system. However, many studies have been focused on improving the fiducial registration accuracy or the target registration accuracy, but few solutions involve optimization model for the distri...

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Published in:Journal of Medical Systems Vol. 44; no. 4; pp. 1 - 12
Main Authors: Lin, Qinyong, Yang, Rongqian, Yang, Lin, Chen, Huazhou, Li, Bohan, Cai, Ken
Format: algorithm diagnostic images equations & formulas pictorial research tables/charts Journal Article
Published: Springer Nature Apr2020
Online Access:View this record in EBSCOhost
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      issn: 01485598
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      dt: Apr2020
      vid: 44
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-020-01548-z
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        atl: Optimization Model for the Distribution of Fiducial Markers in Liver Intervention.
      aug:
        au:
          Lin, Qinyong
          Yang, Rongqian
          Yang, Lin
          Chen, Huazhou
          Li, Bohan
          Cai, Ken
        affil: College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou, China
      sug:
        subj:
          Models, Theoretical
          Prostheses and Implants Methods
          Image Interpretation, Computer Assisted
          Liver Radiography
          Liver Diseases Diagnosis
          Human
          Infrared Therapy Utilization
          Comparative Studies
          Funding Source
      ab: The distribution of fiducial markers is one of the main factors affected the accuracy of optical navigation system. However, many studies have been focused on improving the fiducial registration accuracy or the target registration accuracy, but few solutions involve optimization model for the distribution of fiducial markers. In this paper, we propose an optimization model for the distribution of fiducial markers to improve the optical navigation accuracy. The strategy of optimization model is reducing the distribution from three dimensional to two dimensional to obtain the 2D optimal distribution by using optimization algorithm in terms of the marker number and the expectation equation of target registration error (TRE), and then extend the 2D optimal distribution in two dimensional to three dimensional to calculate the optimal distribution according to the distance parameter and the expectation equation of TRE. The results of the experiments show that the averaged TRE for the human phantom is approximately 1.00 mm by applying the proposed optimization model, and the averaged TRE for the abdominal phantom is 0.59 mm. The experimental results of liver simulator model and ex-vivo porcine liver model show that the proposed optimization model can be effectively applied in liver intervention.
      pubtype: Academic Journal
      doctype:
        algorithm
        diagnostic images
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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