(2019) New image-guided method for localisation of an active capsule endoscope in the stomach. Iet Image Processing. pp. 2321-2327. ISSN 1751-9659
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Abstract
Localisation of an active capsule endoscope inside the stomach has different challenges. One of them is the estimation of the capsule's roll angle. Another challenge is adjusting the distance between the capsule and the stomach to achieve high-quality imaging in the region of interest. In this study, an optimised image-guided localisation (O-Localisation) method is proposed to estimate the roll angle and the scale factor between the consecutive frames. The distance between the capsule and walls of the stomach can be adjusted using the suggested fuzzy adjuster, which is developed based on the estimated scale factors and calibration parameters. This new method is only based on visual information extracted from wireless capsule endoscope video frames. The results show that this method can accurately estimate the rotation angles and scale factors with errors <0.2 for the angles up to 90 degrees and 0.3 for the scales up to 5, respectively. The method is robust to the brightness changes up to 80 with a maximum error of 0.3. The computational time is about 1 s and can be considered near real-time for this application. Accordingly, the O-Localisation method as a real-time, robust and precise method for capsule localisation can provide a more efficient controllable and steerable capsule endoscopes.
Item Type: | Article |
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Keywords: | endoscopes calibration biological organs medical image processing biomedical optical imaging active capsule endoscope high-quality imaging estimated scale factors wireless capsule endoscope video frames steerable capsule endoscopes stomach walls roll angle estimation fuzzy adjuster rotation angle estimation controllable capsule endoscopes image-guided localisation optimisation time 1 0 s Computer Science Engineering Imaging Science & Photographic Technology |
Subjects: | WI Digestive System |
Divisions: | Faculty of Medicine Medical Image and Signal Processing Research Center |
Page Range: | pp. 2321-2327 |
Journal or Publication Title: | Iet Image Processing |
Journal Index: | ISI |
Volume: | 13 |
Number: | 12 |
Identification Number: | https://doi.org/10.1049/iet-ipr.2018.6366 |
ISSN: | 1751-9659 |
Depositing User: | Zahra Otroj |
URI: | http://eprints.mui.ac.ir/id/eprint/10870 |
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