An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features
Joint Authors
Billah, Mustain
Waheed, Sajjad
Rahman, Mohammad Motiur
Source
International Journal of Biomedical Imaging
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-14
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases.
Therefore, early detection and removal of polyps can reduce the possibility of cancer.
Video endoscopy is the most used diagnostic modality for gastrointestinal polyps.
But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps.
Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to.
In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection.
This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps.
Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM).
Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.
American Psychological Association (APA)
Billah, Mustain& Waheed, Sajjad& Rahman, Mohammad Motiur. 2017. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features. International Journal of Biomedical Imaging،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1159718
Modern Language Association (MLA)
Billah, Mustain…[et al.]. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features. International Journal of Biomedical Imaging No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1159718
American Medical Association (AMA)
Billah, Mustain& Waheed, Sajjad& Rahman, Mohammad Motiur. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features. International Journal of Biomedical Imaging. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1159718
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1159718