Martynas Patašius

Model based investigation of retinal vessel tortuosity as a function of blood pressure: preliminary results

Tortuosity is one of parameters which describe a state of the eye fundus blood vessels. Tortuosity can be estimated from the detected vessels in optical fundus images. The increase in vessel tortuosity was observed in eyes of patients with advanced background diabetic retinopathy, papilloedema, even in some completely healthy eyes (in this case tortuosity does not change in time). Though many methods to estimate eye vessel tortuosity exist, dependencies between tortuosity and parameters of cardiovascular system are not fully explored. In this paper we studied whether different tortuosity estimation algorithms can detect the change of blood pressure in the cylindrical segment of the vessel modeled using finite elements method. In addition we studied how does one inhomogeneity added inside the blood vessel influence the tortuosity and what are the relationships between the different tortuosity estimates and blood pressure? We found that even single inhomogeneity of the vessel wall triggers the increase of tortuosity when inner blood pressure increases. The resulting dependencies among different tortuosity estimates and blood pressure are mostly nonlinear.

Ranking of color space components for detection of blood vessels in eye fundus images

Most of the studies so far used the green component of RGB for blood vessel recognition in eye fundus images with some using luminance. However, no study was performed to justify in quantitative manner these choices. We aimed to investigate which color spaces (RGB, YIQ, HSV, HSL, XYZ’) can emphasize vasculature and vascular reflex in order to enable the usage of computationally and conceptionally simpler blood vessel detection methods.

Modification of drusen border detection algorithm based on flooding simulation

Drusen are white or yellow spots in eye fundus that consist of extracellular material. They are a sign of age-related macular degeneration (AMD) - the main cause of blindness in the developed countries and a third main cause of blindness in the whole world. Number and area of drusen are used to grade AMD. However, calculating them manually is time consuming. Thus various methods have been used to detect drusen automatically or semi-automatically. In this paper we propose an alternative method to find the borders of the drusen.

Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation.

Finding Initial Points for Drusen Detection

Drusen are white or yellow spots in eye fundus that consist of extracellular material. They are a sign of age-related macular degeneration – the main cause of blindness in the developed countries and a third main cause of blindness in the whole world. The paper discusses a method to find initial points for drusen detection based on rejection of unsuitable local maximums using high-pass and median filtering.

Integrating Global Data into Local Health Data Base

Data analysis traditionally belong to scientists field of interest. Usually scientists gatherer and analyze their own data. Challenges of 21st century require more global point view in decision making process from each worker in local workplace. Local public health sector is strongly related with global world. So, right managerial decision-making in local workplaces depends on changes in global environment. The speed of changes is very high. Therefore, it is necessary to encourage workers of public health sector to make daily managerial decisions evaluating both global and local data. Information technologies (IT) supports decision making process. It is easier to analyze homogeneous data. Analysis of global data has shown that data formats were often incompatible. Limited IT competencies of public health workers make analysis of data from different sources difficult. This article describes a method for integration of global heterogeneous data in local databases.

Estimation of blurring of optic nerve disc margin

It is known that eye fundus optic nerve disc margins get blurred in papilledema or neuritis. Doctors describe this feature of optic nerve disc by using binary classification “clear margin” or “blurred margin”. We haven’t found studies about quantitative estimation of this phenomenon during our literature analysis.

Multi-scale finite element modeling of 3D printed structures subjected to mechanical loads

Purpose The purpose of this paper is to investigate the influence of geometrical microstructure of items obtained by applying a three-dimensional (3D) printing technology on their mechanical strength. Design/methodology/approach Three-dimensional printed items (3DPI) are composite structures of complex internal constitution. The buildup of the finite element (FE) computational models of 3DPI is based on a multi-scale approach. At the micro-scale, the FE models of representative volume elements corresponding to different additive layer heights and different thicknesses of extruded fibers are investigated to obtain the equivalent non-linear nominal stress–strain curves. The obtained results are used for the creation of macro-scale FE models, which enable to simulate the overall structural response of 3D printed samples subjected to tensile and bending loads. Findings The validation of the models was performed by comparing the computed results against the experimental ones, where satisfactory agreement has been demonstrated within a marked range of thicknesses of additive layers. Certain inadequacies between computed against experimental results were observed in cases of thinnest and thickest additive layers. The principle explanation of the reasons of inadequacies takes into account the poorer quality of mutual adhesion in case of very thin extruded fibers and too-early solidification effect. Originality/value Flexural and tensile experiments are simulated by FE models that are created with consideration to microstructure of 3D printed samples.

LONGITUDINAL USE OF BUSINESS GAME FOR ICT LEARNING FOR STUDYING BUSINESS

The university graduates who are creative find it easier to adapt to the job market and are more useful to the society. Thus, universities should encourage of development of students’ creativity. We noticed that students using business game in each year become more creative compared with students who used business game only one or two times per study program. Longitudinal use of business game has allowed students to understand IT more deeply and has encouraged our students to design a new business game by themselves.

Integration of Multilevel Health Related Data for Generalized Analysis

The modern worker of healthcare must be able to make good decisions in time. Health decision support system requires to perform generalized data analysis. Therefore it is necessary to use data of different types and levels. We found that different organizations tend to use different classifications for their purposes. Thus it is necessary to aggregate those classifications to enable the generalized analysis. For example, evaluation of various types of services on economical point of view makes it necessary to analyse not only each unit of services, but also to simulate aggregated native types of services by changing rules of classification. This task is important for different types of workplaces: politicians, workers of public health sector, workers of municipality, and managers of health care organization. Usually they are not IT professionals.