Informatica

Glaucoma is one of the most insidious eye diseases the occurrence and progression of which a human does not feel. This article provides a brief overview of the eye nerve parameterization methods and algorithms. Parameterization itself is an important task that provides and uniquely defines the structure of the optic nerve disc and further can be used in disease detection or other studies that require a parametric estimate of the eye fundus pattern. So far, planimetric completely automated parameterization of excavation from eye fundus images has not been investigated in detail in the scientific literature. In this article, the authors describe an automated excavation and parameterization algorithm and make the correlation analysis of parameters obtained by both automated and interactive techniques. The obtained results are then compared with those produced by Optical Coherence and Heidelberg Retina Tomography. Finally, the article discusses glaucoma disease detection abilities using the estimated parameters of the eye fundus structures, obtained by different parameterization techniques.

Digital signal processing is one of the most powerful technologies, developed by achievements in science and electronics engineering. Achievements of this technology significantly influenced communications, medicine technique, radiolocation and other. Digital signal processors are usually used for effective solution of digital signal processing problems class. Today digital signal processors are widely used practically in all fields, in which information processing in real-time is needed. Creation of diagnostic medicine systems is one of perspective fields using digital signal processors. The aim of this work was to create digital mathematical model of blood circulation analysis system using digital signal processing instead of analogical nodes of device. In first stage – work algorithm of blood circulation analysis system and mathematical model of blood circulation analysis system in Matlab–Simulink environment was created. In second stage – mathematical model was tested experimentally. Mathematically imitated Doppler signal was sent to tissue and was reflected. The signal was processed in digitally, blood flow direction was marked and blood speed was evaluated. Experimentation was done with real signals that were recorded while investigating patients in eye clinics. Gained results confirmed adequacy of created mathematical model to real analogical blood circulation analysis system (Lizi et al., 2003).

New information technologies provide a possibility of collecting a large amount of fundus images into databases. It allows us to use automated processing and classification of images for clinical decisions. Automated localization and parameterization of the optic nerve disc is particularly important in making a diagnosis of glaucoma, because the main symptoms in these cases are relations between the optic nerve and cupping parameters. This article describes the automated algorithm for the optic nerve disc localization and parameterization by an ellipse within colour retinal images. The testing results are discussed as well.

Application of knowledge discovery in databases (data mining) for medical decision support is discussed in this work. The aim of the study was to use decision support algorithm for the differential diagnosis of intraocular tumors using parameters from eye images obtained by the ultrasound examination. Application of predictive modeling algorithm for decision tree formation using See5.0/C5.0 data mining system is presented. The decision tree was build using tumor geometry and microstructure parameters. The use of decision tree allows to differentiate tumors from other tumor-like formations. Low percentage of diagnostic errors shows that decision tree is reliable enough to offer it as “second opinion” for physician's decision support.