Evaluation of Hepatic Cystic Echinococcosis’ CT image in Xinjiang Uygur Autonomous Region based on Kolmogorov Complexity Model

Abstract

Designing and developing computer-assisted image processing techniques to help doctors improve their diagnosis has received considerable interests over the past years. In this paper, we used the kolmogorov complexity model to analyze the CT images of the healthy liver and multiple daughter hydatid cysts. Before the complexity characteristic calculating, the image preprocessing methods had been used for image standardization. From the kolmogorov complexity model, complexity characteristic were calculated in order to quantify the complexity, between healthy liver and multiple daughter hydatid cysts. Then we use statistical method to analyze the complexity characteristic of those two types of images. Our preliminary results show that the complexity characteristic has statistically significant (p<0.05) to analyze these two types CT images, between the healthy liver and the multiple daughter hydatid cysts. Furthermore, the result leads us to the conclusion that the kolmogorov complexity model could use for analyze the hydatid disease and will also extend the analysis the other lesions of liver.

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J. Zhou, M. Hamit, A. Kutluk, C. Yan, L. Li, J. Chen, Y. Hu, D. Kong and W. Yuan, "Evaluation of Hepatic Cystic Echinococcosis’ CT image in Xinjiang Uygur Autonomous Region based on Kolmogorov Complexity Model," Engineering, Vol. 4 No. 10B, 2012, pp. 57-60. doi: 10.4236/eng.2012.410B015.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Donald P McManus, Wenbao Zhang, Jun Li and Paul B Bartley, “Echinococcosis,” The Lancet, vol. 362, pp. 1295-1304, 2003.
[2] Pedro Moroa and Peter M. Schantzb, “Echinococcosis: a review,” International Journal of Infectious Diseases, vol. 13, pp. 125-133, 2009.
[3] Yu Rong Yang, Tao Sun, Zhengzhi Li et al. “Community surveys and risk factor analysis of human alveolar and cystic echinococcosis in Ningxia Hui Autonomous Region, China,” Bull World Health Organ, vol. 84, no. 9, pp. 714-721.
[4] J. M. Bart, M. Abdukader, Y. L. Zhang, R. Y. Lin, Y. H. Wang, M. Nakao, A. Ito, P. S. Craig, R. Piarroux, D. A. Vuitton and H. Wen, “Genotyping of human cystic echinococcosis in Xinjiang, PR China,” Parasitology, vol. 133, pp. 571-579, 2006.
[5] H Wen, R R New and P S Craig, “Diagnosis and treatment of human hydatidosis,” Br J Clin Pharmacol, vol. 35, pp. 565-574, 1993.
[6] Yalou Zhang, Jean-Mathieu Bart, Patrick Giraudoux, Philip Craig, Dominique Vuitton and Hao Wen, “Morphological and molecular characteristics of Echinococcus multilocularis and Echinococcus granulosus mixed infection in a dog from Xinjiang, China,” Veterinary Parasitology, vol. 139, pp. 244-248, 2006.
[7] Stephens DH, Sheedy PF, Hattery RR and MacCarty RL, “Computed tomography of the liver,” American Journal of Roentgenology, vol. 128, no. 4, pp. 579-590, 1977.
[8] Dionissios D. Karavias, Constantine E. Vagianos, Stavros K. Kakkos, Constantine M. Panagopoulos and John A. Androulakis, “Peritoneal Echinococcosis,” World Journal of Surgery, vol. 20, no. 3, pp. 337-340, 1996.
[9] Sanjeev Subbaramu Ann Q Gates and Vladik Kreinovich, “Application of Kolmogorov Complexity to Image Compression It Is Possible to Have a Better Compression But It Is Not Possible to Have the Best One,” Bull. Eur. Assoc. Theor. Comput. Sci. EATCS, no. 69, pp. 145-150, 1999.
[10] A.N. Kolmogorov, “Three approches to the quantitative definition of information,” Problems of Information Transmission, vol. 2, pp. 1-7, 1965.
[11] F. Kaspar and H.G. Schuster, “Easily calculable measure for the complexity of spatiotemporal patterns,” Physics Review A, vol. 36, no. 2, pp. 842-848, 1987.
[12] A. Lempel and J. Ziv, “On the complexity of finite sequence,” IEEE Trans. Inf. Theory, vol. IT-22, no. 1, pp. 75-81, 1976.
[13] S. Faul, G. Boylan, S. Connolly, W. Marnane and G. Lightbody, “Chaos theory analysis of the newborn EEG - is it worth the wait?”, Proc. WISP, pp. 381–386, 2005.
[14] Jing Hu, Jianbo Gao and Jose Carlos, “Analysis of biomedical signals by the Lempel-Ziv complexity: the effect of finite data size,” IEEE Transaction on Biomedical Engineering, vol. 53, no. 12, pp. 2606-2609, 2006.
[15] Jun KONG and Zheru CHI, “Image Classification Using Kolmogorov Complexity Measure with Randomly Extracted Blocks,” IEICE TRANS. INF. & SYST., vol. E81-D, no. 11, 1998.
[16] Frank Emmert-Streib, “Statistic Complexity: Combining Kolmogorov Complexity with an Ensemble Approach,” Journal of Nervous and Mental Disease, vol. 5, no. 8, pp. e12256, 2010.
[17] O'Gorman, Lawrence, Sanderson, Arthur C. and Preston, Kendall. “A System for Automated Liver Tissue Image Analysis: Methods and Results,” IEEE Transactions on Biomedical Engineering, vol. BME-32, no. 9, pp. 696-706, 1985.
[18] Nugroho H.A., Ihtatho D. and Nugroho H. “Contrast Enhancement for Liver Tumor Identification,” The MIDAS Journal, 2008.

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