JBiSE  Vol.3 No.12 , December 2010
Detection of bleeding patterns in WCE video using TV-Retinex
Author(s) Ming Li
ABSTRACT
The Retinex theory is used to deal with the removal of unfavorable illumination effects from images. In this paper, we present the Retinex theory for bleeding detection in wireless capsule endoscopy (WCE). This processing is quite appropriate to refresh old bleeding region and bleeding region in shadow. A novel total variation model (TV-Retinex) is proposed to solve the Retinex problem quickly; also a support vector machine is employed for classification. Experimental results demonstrate the efficacy of the proposed method.

Cite this paper
nullLi, M. (2010) Detection of bleeding patterns in WCE video using TV-Retinex. Journal of Biomedical Science and Engineering, 3, 1143-1145. doi: 10.4236/jbise.2010.312148.
References
[1]   Ftancis, R.D. (2004) Sensitivity and specificity of the red blood identification (RBIS) in video capsule endoscopy. The 3rd International Conference on Capsule Endoscopy, Miami, FL.

[2]   Baopu, L. (2009) Computer-aided detection of bleeding regions for capsule endoscopy images, IEEE Trans. on Biomedical Engineering, 56, 1032-1039.

[3]   Jobson, D.J., Rahman, Z., and Woodell, G.A. (1997) Properties and performance of a center/surround retinex. IEEE Transactions on Image Processing, 6, 451-462.

[4]   Jobson, D.J., Rahman, Z., and Woodell, G.A. (1997) A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Transactions on Image Processing, 6, 965-976.

[5]   Kimmel, R., Elad, M., Shaked, D., Keshet, R. and Sobel, I. (2003) Variational framework for retinex. International Journal of Computer Vision, 52, 7-23.

[6]   Goldstein, T., and Osher S. (2008) The split bregman method for L1 regularized problems. UCLA CAM Report, 08-29.

[7]   Bregman, L. (1967) The relaxation method of finding the common points of convex sets and its application to the solution of problems in convex optimization. USSR Computational Mathematics and Mathematical Physics, 7, 200-217.

[8]   Weiss, G.M. (2001) The effect of class distribution on classifier learning: An empirical study. Technical Report ML-TR-44, Rutgers University, New Jersey.

 
 
Top