Petr Cermak

Transcranial Sonography of the Substantia Nigra: Digital Image Analysis

BACKGROUND AND PURPOSE: Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers. MATERIALS AND METHODS: One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis. RESULTS: The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement (P < .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively (P < .0001). CONCLUSIONS: The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.

Extreme gravitational lensing in vicinity of Schwarzschild-de Sitter black holes

We have developed a realistic, fully general relativistic computer code to simulate optical projection in a strong, spherically symmetric gravitational field. The standard theoretical analysis of optical projection for an observer in the vicinity of a Schwarzschild black hole is extended to black hole spacetimes with a repulsive cosmological constant, i.e, Schwarzschild-de Sitterspacetimes. Influence of the cosmological constant is investigated for static observers and observers radially free-falling from the static radius. Simulations include effects of the gravitational lensing, multiple images, Doppler and gravitational frequency shift, as well as the intensity amplification. The code generates images of the sky for the static observer and a movie simulations of the changing sky for the radially free-falling observer. Techniques of parallel programming are applied to get a high performance and a fast run of the BHC simulation code.

Semi-automatic Ultrasound Medical Image Recognition for Diseases Classification in Neurology

The main aim of this work is semi-automatic ROI positionig in transcranial medical images based on multi-agent systems (MAS) in preprocessing module. Designed approach is based on image processing and is realized by means of artifical intelligence, MAS, which has been experimentally designed in Matlab software environment. Within this processing has been worked with a set of TCS static images in grayscale and binary representation to experimental testing to positioning. This designed application is used for diseases classification in neurology.

Advantages of using multi-agent principles in FAIL - SAFE UAV system design

In this paper, the possibility of using multi-agent systems principles in design of universal Fail - safe UAV structure is presented. The advantages of this approach and a particular system design are introduced. The benefits of multi-agent approach to design the UAV system are related to its desired properties, which is fail safe feature, meaning the resistance of the system to software and hardware failures. There is also proposed a systems ability to deal with emergency situations and in eventuality of crash, minimal damage caused by accidents. In this context, the ability of “autonomous controlled accident” is described.

Genetic optimization of fuzzy rule based MAS using cognitive analysis

The aim of the contribution is to present Cognitive Analysis of fuzzy rule bases used in Genetic optimization of Multiagent system behaviour. This Cognitive analysis allows to analyze behaviour caused by rules and sort them to Social, Group or Individual sets of the rules. Rules, which have same behaviour, can be reduced. This allows to decrease of the rules and number of genes in chromosome and also GA Search Space. The Fuzzy Rule Based Evolution System is presented. This system consists of three main parts the FUZNET, the GA-MPI and the Webots. Simple example based on the Box Pushing problem is presented.

An Attempt to Teaching Programming with Robots

The aim of the contribution is to present an attempt to teaching programming with robots. Two problems ad methods of their solutions are presented, namely the so called mark identification and following problem and the related method of its solution, and the alleged line following problem, and the corresponding method. The methods for solving the mentioned problems have been implemented on the robotic plat-form Koala. In the paper some comparisons of the two implementations by two groups of students are presented. The two versions are described, and the pros and cons are mentioned for both of two implementations.

How to Detect and Analyze Atherosclerotic Plaques in B-MODE Ultrasound Images: A Pilot Study of Reproducibility of Computer Analysis

This pilot study is focused on recognition and digital analysis of atherosclerotic plaques in ultrasound B-images. The plaques are displayed as differently echogenic regions depending on plaque composition. The first goal is to find significant features to plaque analysis in B-images. We developed software to finding hyperechogenicity of substantia nigra to Parkinson’s Disease evaluation in B-images. We try to discover how to use this software also for atherosclerotic plaques analysis. The software has a function of intelligent brightness detection. We use a set of 23 images, each of them was analyzed five times. The primary goal is to verify the reproducibility of this software to atherosclerotic plaques analysis in medical practice.

Possibilities of Multiagent Simulation Model Application in the Emission Allowances Trading Area

Abstract This paper is focused on possibilities of simulation of emission allowances trading within the EU emission trading system, using new designed multiagent simulation model, which integrates different original soft computing and decision making methods. Firstly, the paper presents the background of the EU emissions trading system and an overview of different methods used in current research connected with CO 2 emission allowances trading. The great contribution of presented paper is the simulation model. This model consists of submodels like model of emission allowances trading of agents – companies and model of ministerial supervision. Each model is described in terms of unconventional modeling methods (like soft computing and decision making methods). In the discussion part, the possibilities of practical usage of created multiagent simulation model in decision making process in companies and public economics are suggested.

The fuzzy-neuro development system FUZNET

The Fuzzy-neural development system is presented in two versions. The First version is the implementation in C, C++ with interface to Matlab or other programs using DLL calling. The second implementation is newer, conform to Referential transparency. For implementation we choose functional programming language Scheme. The Scheme version R5RS is adopted on different platforms like PC, microprocessors and FPGAs. This allows easy transfer of Scheme code on mentioned platforms. There is presented short programming example of Takagi Sugeno Kang fuzzy rule based model in form of the Fuzzy Neural Network. The possible applicatons of the proposed development system are presented.

Component based design of mini UAV

The mini UAV systems design, from the electronic hardware point of view, implies stronger limitations to weight and power consumption. In the case of non-homogenous architecture and different algorithms, we can use a single processor unit like PC or ARM. But in the case of complex algorithm with great amount of data coming from sensors, there is a great problem with stability and real time responses. We present decomposition of the UAV into parts related to sensors, processing, control, communication and drive actuators. Each part can be implemented on FPGA as IP core or programmed on soft processors. This decomposition led to consistency, stability in time and future extensions with minimal problems.