Non-negative Matrix Factorization for Endoscopic Video Summarization
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Identification of ulcers in wireless capsule endoscopy videos
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Local polynomial approximation for unsupervised segmentation of endoscopic images
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
Epitomized summarization of wireless capsule endoscopic videos for efficient visualization
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Capsule endoscopy image analysis using texture information from various colour models
Computer Methods and Programs in Biomedicine
Texture and color based image segmentation and pathology detection in capsule endoscopy videos
Computer Methods and Programs in Biomedicine
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This paper presents a methodology for detecting abnormal patterns in Wireless Capsule Endoscopy (WCE) images. In particular, an average of 50,000 images are obtained during an WCE exam. Usually, these images are reviewed in a form of a video at speeds between 5 to 40 image-frames/sec. The time spent by a physician reading the results of WCE images varies between 45 to 180 minutes. This presents a major problem which is the reading process that consumes a significant amount of time and the results take several days before they become available since the physician has to find the time to study each video uninterrupted for up to 3 hours. The methodology presented here is based on the automatic detection of abnormal WCE patterns in an effort for reducing the reading time of the WCE images and the cost of the procedure as well. The methodology consists of a synergistic integration of image processing, analysis and recognition techniques for achieving the automatic detection of the WCE abnormal patterns.