TY - JOUR
T1 - Videoendoscopic distortion correction and its application to virtual guidance of endoscopy
AU - Helferty, James P.
AU - Zhang, Chao
AU - McLennan, Geoffrey
AU - Higgins, William E.
N1 - Funding Information:
Manuscript received June 15, 2000; revised Apr. 6, 2001. This work was supported in part by the National Cancer Institute of the National Institutes of Health (NIH) under Grant CA-74325 and in part by the Olympus Corporation. An unrefereed preliminary version of this work was presented at the IEEE ICIP Conference, Sept. 2000. Asterisk indicates corresponding author. J. P. Helferty and C. Zhang are with The Pennsylvania State University, Department of Electrical Engineering, University Park, PA 16802 USA. G. McLennan is with the University of Iowa City, Iowa City, IA 52242 USA. *W. E. Higgins is with The Pennsylvania State University, Department of Electrical Engineering, 209 F. Electrical Engineering West, University Park, PA 16802 USA (e-mail: [email protected]). Publisher Item Identifier S 0278-0062(01)05360-5.
PY - 2001/7
Y1 - 2001/7
N2 - 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.
AB - 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.
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U2 - 10.1109/42.932745
DO - 10.1109/42.932745
M3 - Article
C2 - 11465467
AN - SCOPUS:0035384868
SN - 0278-0062
VL - 20
SP - 605
EP - 617
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 7
ER -