Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm

  • Seth D. Billings
  • Ayushi Sinha
  • Austin Reiter
  • Simon Leonard
  • Masaru Ishii
  • Gregory D. Hager
  • Russell H. Taylor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9902)


Functional endoscopic sinus surgery (FESS) is a surgical procedure used to treat acute cases of sinusitis and other sinus diseases. FESS is fast becoming the preferred choice of treatment due to its minimally invasive nature. However, due to the limited field of view of the endoscope, surgeons rely on navigation systems to guide them within the nasal cavity. State of the art navigation systems report registration accuracy of over 1mm, which is large compared to the size of the nasal airways. We present an anatomically constrained video-CT registration algorithm that incorporates multiple video features. Our algorithm is robust in the presence of outliers. We also test our algorithm on simulated and in-vivo data, and test its accuracy against degrading initializations.


Iterative Close Point Contour Error Functional Endoscopic Sinus Surgery Iterative Close Point Structure From Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by NIH R01-EB015530: Enhanced Navigation for Endoscopic Sinus Surgery through Video Analysis and NSF Graduate Research Fellowship Program.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Seth D. Billings
    • 1
  • Ayushi Sinha
    • 1
  • Austin Reiter
    • 1
  • Simon Leonard
    • 1
  • Masaru Ishii
    • 2
  • Gregory D. Hager
    • 1
  • Russell H. Taylor
    • 1
  1. 1.The Johns Hopkins UniversityBaltimoreUSA
  2. 2.Johns Hopkins Medical InstitutionsBaltimoreUSA

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