Abstract
This paper develops a new hybrid electromagnetic-video endoscope 3-D tracking method that introduces anatomical structure constraints and historically observed differential evolution for surgical navigation. Current endoscope tracking approaches still get trapped in image artifacts, tissue deformation, and inaccurate sensor outputs during endoscopic navigation. To deal with these limitations, we spatially constraint inaccurate electromagnetic sensor measurements to the centerlines of anatomical tubular organs (e.g., the airway trees), which can keep the measurements physically inside the tubular organ and tackle the inaccuracy problem caused by respiratory motion and magnetic field distortion. We then propose historically observed differential evolution to precisely fuse the constrained sensor outputs and endoscopic video sequences. The new hybrid tracking framework was evaluated on clinical data, with the experimental results showing that our proposed method fully outperforms current hybrid approaches. In particular, the tracking error was significantly reduced from (5.9 mm, 9.9\(^\circ \)) to (3.3 mm, 8.6\(^\circ \)).
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Acknowledgment
This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant 20720180062, in part by the National Natural Science Foundation of China under Grant 61971367, and in part by the Fujian Provincial Natural Science Foundation under Grant 2020J01112133.
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Luo, X. (2020). A New Electromagnetic-Video Endoscope Tracking Method via Anatomical Constraints and Historically Observed Differential Evolution. In: Martel, A.L., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science(), vol 12263. Springer, Cham. https://doi.org/10.1007/978-3-030-59716-0_10
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DOI: https://doi.org/10.1007/978-3-030-59716-0_10
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