Abstract
Abstract
Purpose
Polyp size is an important factor that may influence diagnosis and clinical management decision, but estimation by visual inspection during endoscopy is often difficult and subject to error. The purpose of this study is to develop a quantitative approach that enables an accurate and objective measurement of polyp size and to study the feasibility of the method.
Methods
We attempted to estimate polyp size and location relative to the gastro-oesophageal junction by integrating data from an electromagnetic tracking sensor and endoscopic images. This method is based on estimation of the three-dimensional coordinates of the borders of the polyp by combining the endoscope camera position and the corresponding points along the polyp border in endoscopic images using a computer vision-based algorithm. We evaluated the proposed method using a simulated upper gastrointestinal endoscopy model.
Results
The difference between the mean of ten measurements of one artificial polyp and its actual size (10 mm in diameter) was 0.86 mm. Similarly, the difference between the mean of ten measurements of the polyp distance from the gastroesophageal junction and its actual distance (~ 22 cm) was 1.28 mm. Our results show that the changes in camera positions in which the images were taken and the quality of the polyp segmentation have the most impact on the accuracy of polyp size estimation.
Conclusion
This study demonstrated an innovative approach to endoscopic measurements using motion tracking technologies and computer vision and demonstrated its accuracy in determining the size and location of the polyp. The observed magnitude of error is clinically acceptable, and the measurements are available immediately after the images captured. To enhance accuracy, it is recommended to avoid identical images and instead utilise control wheels on the endoscope for capturing different views. Future work should further evaluate this innovative method during clinical endoscopic procedures.
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Cited by
1 articles.
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