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∘) to (3.3 mm, 8.6∘).
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CITATION STYLE
Luo, X. (2020). A New Electromagnetic-Video Endoscope Tracking Method via Anatomical Constraints and Historically Observed Differential Evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12263 LNCS, pp. 96–104). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59716-0_10
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