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

doi:10.1007/978-3-319-46726-9_16

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

Computer Vision and Pattern Recognition 2016-10-26 v1

Authors: Seth D. Billings , Ayushi Sinha , Austin Reiter , Simon Leonard , Masaru Ishii , Gregory D. Hager , Russell H. Taylor

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Abstract

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.

Keywords

surgical robotics surgical robot medical image analysis

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@article{arxiv.1610.07931,
  title  = {Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm},
  author = {Seth D. Billings and Ayushi Sinha and Austin Reiter and Simon Leonard and Masaru Ishii and Gregory D. Hager and Russell H. Taylor},
  journal= {arXiv preprint arXiv:1610.07931},
  year   = {2016}
}

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8 pages, 4 figures, MICCAI

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

Abstract

Keywords

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