To assist the insertion of a robot-aided endoscope during colonoscopy, a measuring system is required so that the endoscope tip can align automatically and thus find the curved pathway of the large intestine. To achieve this, a self-expanding nitinol wire basket is used to sense the contour of the intestine. As the wire basket touches the wall, it is deflected towards the center of the intestine. The relative position of the wire basket within the camera image is captured, which describes the desired direction to follow the organ. To identify the wire basket in the image, the original RGB image stream is converted into the HSV (hue, saturation, value) color space. Thus, a binary image can be created, in which only the neon-green color portion of the wire basket is visible as a cross. The Hough Transformation is used to search for straight lines in the binary image. Once two lines are found, the intersection point can be calculated and thus its position in the image. The evaluation of the execution time of the algorithm on a live stream was 45 ± 31 ms on average. The algorithm robustly recognizes the wire basket even if it was not visible to the human eye in the original RGB image due to deficient lighting.
%0 Conference Paper
%1 giacoppo2021finding
%A Giacoppo, Giuliano
%A Mammel, Rebecca
%A Pott, Peter P.
%D 2021
%J Current Directions in Biomedical Engineering
%K myown
%N 2
%P 215-218
%R https://doi.org/10.1515/cdbme-2021-2055
%T Finding the curved pathway of the large intestine for robot-aided colonoscopy
%V 7
%X To assist the insertion of a robot-aided endoscope during colonoscopy, a measuring system is required so that the endoscope tip can align automatically and thus find the curved pathway of the large intestine. To achieve this, a self-expanding nitinol wire basket is used to sense the contour of the intestine. As the wire basket touches the wall, it is deflected towards the center of the intestine. The relative position of the wire basket within the camera image is captured, which describes the desired direction to follow the organ. To identify the wire basket in the image, the original RGB image stream is converted into the HSV (hue, saturation, value) color space. Thus, a binary image can be created, in which only the neon-green color portion of the wire basket is visible as a cross. The Hough Transformation is used to search for straight lines in the binary image. Once two lines are found, the intersection point can be calculated and thus its position in the image. The evaluation of the execution time of the algorithm on a live stream was 45 ± 31 ms on average. The algorithm robustly recognizes the wire basket even if it was not visible to the human eye in the original RGB image due to deficient lighting.
@inproceedings{giacoppo2021finding,
abstract = {To assist the insertion of a robot-aided endoscope during colonoscopy, a measuring system is required so that the endoscope tip can align automatically and thus find the curved pathway of the large intestine. To achieve this, a self-expanding nitinol wire basket is used to sense the contour of the intestine. As the wire basket touches the wall, it is deflected towards the center of the intestine. The relative position of the wire basket within the camera image is captured, which describes the desired direction to follow the organ. To identify the wire basket in the image, the original RGB image stream is converted into the HSV (hue, saturation, value) color space. Thus, a binary image can be created, in which only the neon-green color portion of the wire basket is visible as a cross. The Hough Transformation is used to search for straight lines in the binary image. Once two lines are found, the intersection point can be calculated and thus its position in the image. The evaluation of the execution time of the algorithm on a live stream was 45 ± 31 ms on average. The algorithm robustly recognizes the wire basket even if it was not visible to the human eye in the original RGB image due to deficient lighting.},
added-at = {2021-11-09T21:02:11.000+0100},
author = {Giacoppo, Giuliano and Mammel, Rebecca and Pott, Peter P.},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/22668b36f5bf991a62e10a96574b825a4/peterpott},
doi = {https://doi.org/10.1515/cdbme-2021-2055},
interhash = {db7badef9f89ebc14b4e0864982b844c},
intrahash = {2668b36f5bf991a62e10a96574b825a4},
journal = {Current Directions in Biomedical Engineering},
keywords = {myown},
number = 2,
pages = {215-218},
timestamp = {2022-02-24T15:30:36.000+0100},
title = {Finding the curved pathway of the large intestine for robot-aided colonoscopy},
volume = 7,
year = 2021
}
