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Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy
Joint Authors
Si, Jianmin
Wang, Bin
Hu, Weiling
Liu, Jiquan
Duan, Huilong
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-24
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Gastroscopic examination is one of the most common methods for gastric disease diagnosis.
In this paper, a multitarget tracking approach is proposed to assist endoscopists in identifying lesions under gastroscopy.
This approach analyzes numerous preobserved gastroscopic images and constructs a gastroscopic image graph.
In this way, the deformation registration between gastroscopic images is regarded as a graph search problem.
During the procedure, the endoscopist marks suspicious lesions on the screen and the graph is utilized to locate and display the lesions in the appropriate frames based on the calculated registration model.
Compared to traditional gastroscopic lesion surveillance methods (e.g., tattooing or probe-based optical biopsy), this approach is noninvasive and does not require additional instruments.
In order to assess and quantify the performance, this approach was applied to stomach phantom data and in vivo data.
The clinical experimental results demonstrated that the accuracy at angularis, antral, and stomach body was 6.3 ± 2.4 mm, 7.6 ± 3.1 mm, and 7.9 ± 1.6 mm, respectively.
The mean accuracy was 7.31 mm, average targeting time was 56 ms, and the P value was 0.032, which makes it an attractive candidate for clinical practice.
Furthermore, this approach provides a significant reference for endoscopic target tracking of other soft tissue organs.
American Psychological Association (APA)
Wang, Bin& Hu, Weiling& Liu, Jiquan& Si, Jianmin& Duan, Huilong. 2014. Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016847
Modern Language Association (MLA)
Wang, Bin…[et al.]. Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1016847
American Medical Association (AMA)
Wang, Bin& Hu, Weiling& Liu, Jiquan& Si, Jianmin& Duan, Huilong. Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016847
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016847