Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30578
Improvement of Blood Detection Accuracy using Image Processing Techniques suitable for Capsule Endoscopy

Authors: Gilwon Yoon, Yong-Gyu Lee

Abstract:

Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.

Keywords: Image Processing, capsule endoscopy, blood detection

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060916

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385

References:


[1] D. G. Adler and C. J. Gostout, "Wireless Capsule Endoscopy", Hospital Physician, 2003, pp.14-22.
[2] A. karargyris and N. Bourbakis, "ASurvey on WCE Imaging Systems and Techniques," IEEE Engineering in Medicine and Biology Magazine, Vol. 29, no. 1, 2010
[3] L. Cui, C. Hu, Y. Zou, and M. Q.-H. Meng, "Bleeding Detection in Wireless Capsule Endoscopy Images by Support Vector Classifier" in 2010 IEEE Int. Conf. on Information and Automation (ICIA), 2010, pp. 1746-1751.
[4] A. Kararhyris, and N. Bourbakis, "A Methodology for Detecting Blood-based Abnormalities in Wireless Capsule Endoscopy Videos" in 8th IEEE Int. Conf. on Bioinformatics and Bio Engineering (BIBE-08), 2008, pp. 1-6.
[5] Y.G. Lee, and G. Yoon., "Bleeding Detection algorithm for capsule endoscopy", International Journal of Biological and Life Sciences,
[6] Y.G. Lee, and G. Yoon., "Real-time image analysis of capsule endoscopy for bleeding discrimination in embedded system platform", International Journal of Biological and Life Sciences, World Academy of Science, Engineering and Technology, 2011, 60:1030-1034.
[7] B. Giritharan, X. Yuan, J. Liu, B. Buckles, J. Oh and S. J. Tang, “Bleeding Detection from Capsule Endoscopy Videos,” in 30th Annul. IEEE EBMS Conf., Vancouver, 2008, pp. 4780-4783.