Title :
Capsule endoscopy video Boundary Detection
Author :
Li, Baopu ; Meng, Max Q -H
Author_Institution :
Shenzhen Inst. of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China
Abstract :
Capsule endoscopy (CE) is a recently developed new technology which enables direct visualization of the inner tract of the whole small bowel (SB) in human body. Due to such a breakthrough compared to traditional endoscopy imaging modalities, this device with its size close to a small pill has seen its wide application in hospitals since it was approved for marketing in 2001. However, it is reported that the inspection of the video data produced in each test cost a clinician about two hours on average to examine. To mitigate such a burden for physicians, it is necessary to develop automatic video analysis techniques for CE video. Since a CE video has an average length of about 60,000 frames for each test, it may be beneficial to segment such a long video into meaningful parts. In this study, we investigate the possibility of applying video boundary detection methods for this purpose. Color and textural features are utilized to represent the visual content. The CE video boundary detection is then formulated as a problem of finding local maximal value along the dissimilarity curve for a CE video. Since a CE undergoes a chaotic motion originated from peristalsis of the digestive tract, motion analysis is further taken into account to refine the results produced in the above steps. Preliminary experimental results suggest the possible usage of the proposed scheme for CE video segmentation.
Keywords :
endoscopes; image colour analysis; image segmentation; medical image processing; CE video segmentation; automatic video analysis technique; capsule endoscopy video boundary detection method; color feature; dissimilarity curve; endoscopy imaging modality; motion analysis; textural feature; Cameras; Color; Diseases; Feature extraction; Histograms; Image color analysis; Motion segmentation; Capsule endoscopy; color; motion; texture; video segmentation;
Conference_Titel :
Information and Automation (ICIA), 2011 IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4577-0268-6
Electronic_ISBN :
978-1-4577-0269-3
DOI :
10.1109/ICINFA.2011.5949020