NDLI: Contourlet based feature extraction and classification for Wireless Capsule Endoscopic images

Content Provider	IEEE Xplore Digital Library
Author	Chen Junzhou He Run Zhang Li Peng Qiang Gan Tao
Copyright Year	2011
Description	Author affiliation: Department of Computer Science and Technology, Southwest Jiaotong University, ChengDu, China (Chen Junzhou; He Run; Zhang Li; Peng Qiang) \|\| Digestive Endoscopic Center, West China Hospital, Sichuan University (Gan Tao)
Abstract	Wireless Capsule Endoscopy (WCE) is a late-model non-invasive device to detect abnormalities in small intestine. The traditional diagnostic method that only depending on clinicians' naked eyes is time-consuming and labor-intensive. It is necessary to develop a computer-aided system to alleviate the burden of clinicians. In this paper, a new color-texture feature extraction method is proposed for the classification of normal and abnormal WCE tissue images. The Contourlet Transform is introduced and used for each color channel of each WCE image in HSV color space. Finally, we construct a 288-dimensions feature vector by calculating the 3-order color moments for each baseband generated by using the Contourlet Transform. Real experiments using different classifiers in various color spaces are implemented to evaluate the performance of the proposed method.
Starting Page	219
Ending Page	223
File Size	1848622
Page Count	5
File Format	PDF
ISBN	9781424493517
e-ISBN	9781424493524
DOI	10.1109/BMEI.2011.6098233
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Intestines Image color analysis Endoscopes Transforms The Contourlet Transform Feature extraction Hemorrhaging Feature Extraction and Classification Wireless Capsule Endoscopy
Content Type	Text
Resource Type	Article

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