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A markerless automatic deformable registration framework for augmented reality navigation of laparoscopy partial nephrectomy

  • Xiaohui Zhang
  • Junchen Wang
  • Tianmiao Wang
  • Xuquan Ji
  • Yu Shen
  • Zhen Sun
  • Xuebin ZhangEmail author
Original Article
  • 209 Downloads

Abstract

Purpose Video see-through augmented reality (VST-AR) navigation for laparoscopic partial nephrectomy (LPN) can enhance intraoperative perception of surgeons by visualizing surgical targets and critical structures of the kidney tissue. Image registration is the main challenge in the procedure. Existing registration methods in laparoscopic navigation systems suffer from limitations such as manual alignment, invasive external marker fixation, relying on external tracking devices with bulky tracking sensors and lack of deformation compensation. To address these issues, we present a markerless automatic deformable registration framework for LPN VST-AR navigation.

Method

Dense stereo matching and 3D reconstruction, automatic segmentation and surface stitching are combined to obtain a larger dense intraoperative point cloud of the renal surface. A coarse-to-fine deformable registration is performed to achieve a precise automatic registration between the intraoperative point cloud and the preoperative model using the iterative closest point algorithm followed by the coherent point drift algorithm. Kidney phantom experiments and in vivo experiments were performed to evaluate the accuracy and effectiveness of our approach.

Results

The average segmentation accuracy rate of the automatic segmentation was 94.9%. The mean target registration error of the phantom experiments was found to be 1.28 ± 0.68 mm (root mean square error). In vivo experiments showed that tumor location was identified successfully by superimposing the tumor model on the laparoscopic view.

Conclusion

Experimental results have demonstrated that the proposed framework could accurately overlay comprehensive preoperative models on deformable soft organs automatically in a manner of VST-AR without using extra intraoperative imaging modalities and external tracking devices, as well as its potential clinical use.

Keywords

Surgical navigation Augmented reality Video see-through Dense 3D reconstruction Deformable registration 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61701014).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© CARS 2019

Authors and Affiliations

  1. 1.School of Mechanical Engineering and AutomationBeihang UniversityBeijingChina
  2. 2.Beijing Advanced Innovation Center for Biomedical EngineeringBeihang UniversityBeijingChina
  3. 3.Department of Urology, Peking Union Medical College HospitalPeking Union Medical College and Chinese Academy of Medical SciencesBeijingChina

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