Database design and implementation for a digestive tract diagnostics support system

Jan Cychnerski, Adam Brzeski, Adam Blokus, Tomasz Dziubich, Mateusz Jędrzejewski


The article briefly presents the process of diagnosing gastrointestinal diseases and discusses existing techniques of supporting it with automatic analysis of video from gastrointestinal examinations. Further, the process of designing a specialized medical database is described. The main goal of the created database is to provide data for the training of automatic classifiers of gastrointestinal diseases. Finally, the collected data and acquired results are presented.


medical database; wireless capsule endoscopy; image recognition

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Karargyris A., Bourbakis N.: Wireless capsule endoscopy and endoscopic imaging: a survey on various methodologies presented. Engineering in Medicine and Biology Magazine, IEEE, Vol. 29(1), 2010, s. 72÷83.

Kodogiannis V. S., Boulougoura M.: An Adaptive Neurofuzzy Approach for the Diagnosis in Wireless Capsule Endoscopy Imaging. International Journal of Information Technology, Vol. 13, No. 1, 2007.

Vilarino F., Spyridonos P., Pujol O., Vitria J., Radeva P.: Automatic detection of intestinal juices in wireless capsule video endoscopy. Proc. 18th Int. Conf. Pattern Recognition, Vol. 4, Universitat Autonoma de Barcelona, Spain 2006, s. 719÷722.

Krawczyk H., Betlej L., Pielaszkiewicz T., Rutkowski Sz.: Design problems of endoscopy recommendation system. J. of Medical Informatic Technologies, 5:IT3 - IT11, 2000.

Minimal Standard Terminology for gastrointestinal endoscopy. Organization Mondiale Endoscopia Digestive,

Li B., Meng M.: Small Bowel Tumor Detection for Wireless Capsule Endoscopy Images Using Textural Features and Support Vector Machine. The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Cychnerski J.: Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel. 5th International Academic Conference of Students, Ph.D. Students and Young Scientists Computer Science & Engineering, 2011.