Paper
21 March 2016 Image-based navigation for functional endoscopic sinus surgery using structure from motion
Simon Leonard, Austin Reiter, Ayushi Sinha, Masaru Ishii, Russell H. Taylor, Gregory D. Hager
Author Affiliations +
Abstract
Functional Endoscopic Sinus Surgery (FESS) is a challenging procedure for otolaryngologists and is the main surgical approach for treating chronic sinusitis, to remove nasal polyps and open up passageways. To reach the source of the problem and to ultimately remove it, the surgeons must often remove several layers of cartilage and tissues. Often, the cartilage occludes or is within a few millimeters of critical anatomical structures such as nerves, arteries and ducts. To make FESS safer, surgeons use navigation systems that register a patient to his/her CT scan and track the position of the tools inside the patient. Current navigation systems, however, suffer from tracking errors greater than 1 mm, which is large when compared to the scale of the sinus cavities, and errors of this magnitude prevent from accurately overlaying virtual structures on the endoscope images. In this paper, we present a method to facilitate this task by 1) registering endoscopic images to CT data and 2) overlaying areas of interests on endoscope images to improve the safety of the procedure. First, our system uses structure from motion (SfM) to generate a small cloud of 3D points from a short video sequence. Then, it uses iterative closest point (ICP) algorithm to register the points to a 3D mesh that represents a section of a patients sinuses. The scale of the point cloud is approximated by measuring the magnitude of the endoscope's motion during the sequence. We have recorded several video sequences from five patients and, given a reasonable initial registration estimate, our results demonstrate an average registration error of 1.21 mm when the endoscope is viewing erectile tissues and an average registration error of 0.91 mm when the endoscope is viewing non-erectile tissues. Our implementation SfM + ICP can execute in less than 7 seconds and can use as few as 15 frames (0.5 second of video). Future work will involve clinical validation of our results and strengthening the robustness to initial guesses and erectile tissues.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Simon Leonard, Austin Reiter, Ayushi Sinha, Masaru Ishii, Russell H. Taylor, and Gregory D. Hager "Image-based navigation for functional endoscopic sinus surgery using structure from motion", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97840V (21 March 2016); https://doi.org/10.1117/12.2217279
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CITATIONS
Cited by 17 scholarly publications.
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KEYWORDS
Endoscopes

Computed tomography

Surgery

Video

Endoscopy

Navigation systems

Image segmentation

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