27 February 2010 Automatic feature detection for 3D surface reconstruction from HDTV endoscopic videos
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A growing number of applications in the field of computer-assisted laparoscopic interventions depend on accurate and fast 3D surface acquisition. The most commonly applied methods for 3D reconstruction of organ surfaces from 2D endoscopic images involve establishment of correspondences in image pairs to allow for computation of 3D point coordinates via triangulation. The popular feature-based approach for correspondence search applies a feature descriptor to compute high-dimensional feature vectors describing the characteristics of selected image points. Correspondences are established between image points with similar feature vectors. In a previous study, the performance of a large set of state-of-the art descriptors for the use in minimally invasive surgery was assessed. However, standard Phase Alternating Line (PAL) endoscopic images were utilized for this purpose. In this paper, we apply some of the best performing feature descriptors to in-vivo PAL endoscopic images as well as to High Definition Television (HDTV) endoscopic images of the same scene and show that the quality of the correspondences can be increased significantly when using high resolution images.
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Anja Groch, Anja Groch, Matthias Baumhauer, Matthias Baumhauer, Hans-Peter Meinzer, Hans-Peter Meinzer, Lena Maier-Hein, Lena Maier-Hein, } "Automatic feature detection for 3D surface reconstruction from HDTV endoscopic videos", Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76251P (27 February 2010); doi: 10.1117/12.845645; https://doi.org/10.1117/12.845645

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