Title :
Edge cross-section features for detection of appendiceal orifice appearance in colonoscopy videos
Author :
Wang, Yi ; Tavanapong, Wallapak ; Wong, Johnny ; Oh, JungHwan ; De Groen, Piet C.
Author_Institution :
Department of Computer Science, Iowa State University, Ames, 50011, USA
Abstract :
Colonoscopy is an endoscopic technique that allows a physician to inspect the inside of the human colon. The appearance of the appendiceal orifice during colonoscopy indicates a complete traversal of the colon, which is one of important quality indicators of examination of the colon. In this paper, we propose a new algorithm that detects appendix images—images showing the appendiceal orifice. We introduce new features based on geometric shape, saturation and intensity changes along the norm direction (cross-section) of an edge to discriminate appendix images. Our experimental results on real colonoscopic images show the average sensitivity and specificity of 88.12% and 94.25%, respectively.
Keywords :
Cancer; Colon; Colonoscopy; Computer vision; Endoscopes; Guidelines; Image edge detection; Orifices; Shape; Videos; Algorithms; Appendix; Artificial Intelligence; Bayes Theorem; Colon; Colonoscopy; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Surgery, Computer-Assisted; Video Recording;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4649834