Details

Autor(en) / Beteiligte

• Xiaoying Liu
• Jia Gu
• Yaoqin Xie
• Jun Xiong
• Wenjian Qin

Titel

A new approach to detecting ulcer and bleeding in Wireless capsule endoscopy images

Ist Teil von

• Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics, 2012, p.737-740

Ort / Verlag

IEEE

Erscheinungsjahr

2012

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Xplore Digital Library

Beschreibungen/Notizen

• In recent years, Wireless capsule endoscopy (WCE) has been widely utilized in diagnosis of gastrointestinal (GI) tract disease. This new technology is painless and can see small intestine that traditional endoscopies cannot reach. However, Analysis of massive images for each WCE detection is tedious and time consuming to physicians. In this paper we present a computer-aid approach to help clinicians to discriminate amongst regions of normal or abnormal tissue. We use covariance of second-order statistical features which called as color wavelet covariance (CWC), based on discrete wavelet transform (DWT) and then optimize them by a selected algorithm. Accurate image segmentation and classification is achieved by a joint classifier, which is obtained by Texton Boost classifier. The whole approach has been validated on various WCE data and achieves a good result.