Paper
30 April 2004 Automatic extraction and visualization of human inner structures from endoscopic image sequences
Chia-Hsiang Wu, Yi-Chiao Chen, Chun-Yen Liu, Chien-Chen Chang, Yung-Nien Sun
Author Affiliations +
Abstract
Most of the three-dimensional (3-D) reconstructions of human organs rely on medical volume data. In this paper, we propose to use the endoscopic image sequences as a new image modality for surface reconstruction of human organs or tissues. Using the pinhole camera model, the original 3-D points are projected to two-dimensional (2-D) images by multiplying transformation matrices. We assume the intrinsic camera parameters, such as the focal length and principal points, are known and simplify the transformation matrices to only include the camera motion, i.e. camera rotation and translation. Using the factorization method for recovering the shape of the object and the motion of the camera from an image sequence, the 3-D structures are computed. 3-D reconstruction from endoscopic image sequences is a new exploration. It provides additional information that facilitates the understanding for the lesion areas three-dimensionally. And the reconstructed structures directly correspond to the original images and can be rendered with precise texture-mapping easily. It has potential to be used to guide surgery and serve as an alternative data source for constructing new stereo endoscopy systems using one camera.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chia-Hsiang Wu, Yi-Chiao Chen, Chun-Yen Liu, Chien-Chen Chang, and Yung-Nien Sun "Automatic extraction and visualization of human inner structures from endoscopic image sequences", Proc. SPIE 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, (30 April 2004); https://doi.org/10.1117/12.535880
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CITATIONS
Cited by 19 scholarly publications and 1 patent.
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KEYWORDS
Endoscopy

Cameras

3D image processing

3D modeling

3D image reconstruction

Surgery

Imaging systems

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