Endoscopic navigation in the absence of CT imaging
This addresses the challenge for clinicians performing endoscopic explorations in the nasal cavity and sinuses when reference CT images are unavailable, representing an incremental improvement by adapting existing methods to a specific clinical scenario.
The paper tackles the problem of endoscopic navigation without CT imaging by using shape statistics from past CT scans and a deformable registration algorithm, achieving submillimeter registrations in in-vivo clinical data and assigning confidence to these registrations.
Clinical examinations that involve endoscopic exploration of the nasal cavity and sinuses often do not have a reference image to provide structural context to the clinician. In this paper, we present a system for navigation during clinical endoscopic exploration in the absence of computed tomography (CT) scans by making use of shape statistics from past CT scans. Using a deformable registration algorithm along with dense reconstructions from video, we show that we are able to achieve submillimeter registrations in in-vivo clinical data and are able to assign confidence to these registrations using confidence criteria established using simulated data.