Correction of distortion in endoscope images

Smith, Warren E.; Vakil, Nimish B.; Maislin, S.A.

doi:10.1109/42.126918

Cited by 90 publications

(45 citation statements)

References 2 publications

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“…Such models were for example applied for endoscope calibration, see [17,204,454,565]. Other calibration approaches using such models are [8,42,134,148,215,216,274,302,330,381,436,437,514,515,521,525,534].…”

Section: Inversion Of Modelsmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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A printed and bound version is available at a special discount price of US35 from Now Publishers. This can be obtained by entering the promotional code CGV006023 on https://www.nowpublishers.com/bookorder.aspx?doi=0600000023&product=CGVInternational audienceThis survey is mainly motivated by the increased availability and use of panoramic image acquisition devices, in computer vision and various of its applications. Different technologies and different computational models thereof exist and algorithms and theoretical studies for geometric computer vision ("structure-from-motion") are often re-developed without highlighting common underlying principles. One of the goals of this survey is to give an overview of image acquisition methods used in computer vision and especially, of the vast number of camera models that have been proposed and investigated over the years, where we try to point out similarities between different models. Results on epipolar and multi-view geometry for different camera models are reviewed as well as various calibration and self-calibration approaches, with an emphasis on non-perspective cameras. We finally describe what we consider are fundamental building blocks for geometric computer vision or structure-from-motion: epipolar geometry, pose and motion estimation, 3D scene modeling, and bundle adjustment. The main goal here is to highlight the main principles of these, which are independent of specific camera models

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Section: Inversion Of Modelsmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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“…Although nonlinear magnification of the distorted endoscopic image in two dimensions is needed to correct the barrel distortion, the assumption precludes the loss of generality as a typical endoscope lens is circularly symmetric within narrow precision limits [11]. This assumption simplifies the model by converting a 2-D distortion problem into a onedimensional (1-D) problem.…”

Section: Theoretical Modelmentioning

confidence: 99%

“…Hence, two optimum polynomial coefficients are computed using (9). A normalized error function is defined as the normalized sum of magnitudes of the perpendiculars drawn from each of the points on the best linear fit of th column as (10) The total error for the whole grid image is obtained by (11) In the ideal condition, when there is no distortion in the image, the total error is zero since all grid lines will be imaged as straight lines. However, due to image distortion, has a positive value which decreases monotonously as the distortion reduces.…”

Section: A Estimation Of Expansion Coefficientsmentioning

confidence: 99%

“…All the above models give reasonable results for images obtained from cameras with normal viewing objective lenses, but these models are not effective for electronic endoscopes which use wide-angle lens cameras. Smith et al [11] gave a formulation in which distortion was assumed to be purely radial, and orthogonal Chebyshev polynomials were used to determine the model parameters. Hideaki et al [12] presented a different method for estimation of the model parameters, in which a moment matrix was obtained from a set of image points, and distorted grid lines in the image were straightened on the basis of the smallest characteristic root of the moment matrix.…”

Section: Inimally Invasive Therapy (Mit) Is Increasinglymentioning

confidence: 99%

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A new approach for nonlinear distortion correction in endoscopic images based on least squares estimation

Asari¹,

Kumar

Radhakrishnan

1999

IEEE Trans. Med. Imaging

104

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Abstract-Images captured with a typical endoscope show spatial distortion, which necessitates distortion correction for subsequent analysis. In this paper, a new methodology based on least squares estimation is proposed to correct the nonlinear distortion in the endoscopic images. A mathematical model based on polynomial mapping is used to map the images from distorted image space onto the corrected image space. The model parameters include the polynomial coefficients, distortion center, and corrected center. The proposed method utilizes a line search approach of global convergence for the iterative procedure to obtain the optimum expansion coefficients. A new technique to find the distortion center of the image based on curvature criterion is presented. A dual-step approach comprising token matching and integrated neighborhood search is also proposed for accurate extraction of the centers of the dots contained in a rectangular grid, used for the model parameter estimation. The model parameters were verified with different grid patterns. The distortion-correction model is applied to several gastrointestinal images and the results are presented. The proposed technique provides high-speed response and forms a key step toward online camera calibration, which is required for accurate quantitative analysis of the images.

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“…These systems superimpose virtual and real endoscopic images accurately. Previous studies have investigated additional parameters for endoscopic camera calibration other than those in the conventional Tsai's method [4], and the correction of distortion caused by wide-angle lenses is often incorporated [5], [6], [7], [8]. Moreover, the zoom and focus parameters for microscopes have been examined for microscopic camera calibration [9].…”

Section: Introductionmentioning

confidence: 99%

Camera Model and Calibration Procedure for Oblique-Viewing Endoscope

Yamaguchi

Nakamoto

Sato

et al. 2003

Lecture Notes in Computer Science

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Abstract. Oblique-viewing endoscopes (oblique scopes) are widely used medically. It is essential for certain procedures such as laparoscopy, arthroscopy, and sinus endoscopy. In an oblique scope, its viewing directions are changeable by rotating the scope cylinder. Although a camera calibration method is necessary to apply augmented reality technologies to oblique endoscopic procedures, no method for oblique scope calibration has been developed yet. In the present paper, we formulate a camera model and a calibration procedure for oblique scopes. In the calibration procedure, Tsai's calibration is performed at zero-rotation of the scope cylinder, and then the variation of the external camera parameters corresponding to the rotation of the scope cylinder is modeled and estimated as a function of the rotation angle. Accurate estimation of the rotational axis is included in the procedure. The precision of this estimation was demonstrated to have a significant effect on the overall calibration accuracy in the experimental evaluation especially with large rotation angles. The projection error in the image plane was around two pixels. The proposed method was shown to be clinically applicable.

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Correction of distortion in endoscope images

Cited by 90 publications

References 2 publications

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

A new approach for nonlinear distortion correction in endoscopic images based on least squares estimation

Camera Model and Calibration Procedure for Oblique-Viewing Endoscope

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