Endoscopic navigation in the absence of CT imaging

TL;DR

This paper introduces a navigation system for endoscopic procedures that operates without CT scans by utilizing shape statistics and dense video reconstructions, achieving accurate registration in clinical settings.

Contribution

It presents a novel method combining shape statistics and deformable registration to enable endoscopic navigation without CT imaging.

Findings

Achieved submillimeter registration accuracy in vivo.

Successfully used confidence criteria to validate registrations.

Demonstrated system effectiveness in clinical data.

Abstract

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.