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.

has been cited by the following article:

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

  AUTHORS: Jingjing Zhou, Murat Hamit, Abdugheni Kutluk, Chuanbo Yan, Li Li, Jianjun Chen, Yanting Hu, Dewei Kong, Weikang Yuan

  KEYWORDS: Hepatic Cystic Echinococcosis; CT image; Kolmogorov Complexity

  JOURNAL NAME: Engineering, Vol.4 No.10B, January 17, 2013

  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