title: Videoendoscopic distortion correction and its application to virtual guidance of endoscopy.
abstract: Modern video-based endoscopes offer physicians a wide-angle field of view (FOV) for minimally invasive procedures. Unfortunately, inherent barrel distortion prevents accurate perception of range. This makes measurement and distance judgment difficult and causes difficulties in emerging applications, such as virtual guidance of endoscopic procedures. Such distortion also arises in other wide FOV camera circumstances. This paper presents a distortion-correction technique that can automatically calculate correction parameters, without precise knowledge of horizontal and vertical orientation. The method is applicable to any camera-distortion correction situation. Based on a least-squares estimation, our proposed algorithm considers line fits in both FOV directions and gives a globally consistent set of expansion coefficients and an optimal image center. The method is insensitive to the initial orientation of the endoscope and provides more exhaustive FOV correction than previously proposed algorithms. The distortion-correction procedure is demonstrated for endoscopic video images of a calibration test pattern, a rubber bronchial training device, and real human circumstances. The distortion correction is also shown as a necessary component of an image-guided virtual-endoscopy system that matches endoscope images to corresponding rendered three-dimensional computed tomography views.
authors.affiliation: The Pennsylvania State University, Department of Electrical Engineering, University Park 16802, USA.
authors.forename: J P
authors.initials: JP
authors.lastname: Helferty
authors.forename: C
authors.initials: C
authors.lastname: Zhang
authors.forename: G
authors.initials: G
authors.lastname: McLennan
authors.forename: W E
authors.initials: WE
authors.lastname: Higgins
mesh_terms: D016477:Artifacts; D001999:Bronchoscopy; D002138:Calibration; D003198:Computer Simulation; D004724:Endoscopy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008433:Mathematics; D010364:Pattern Recognition, Visual; D020535:Video-Assisted Surgery / Q000379:methods*