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On Validation of Algorithms for Dynamic Medical Data Separation
Tichý, Ondřej
The problem of dynamic medical image sequence separation is studied. We introduced the state of the art algorithms for medical sequence decomposition together with those that are proposed by us. The validation and the comparison of the algorithms are nontrivial and challenging task. We propose to use a synthetic data where a ground truth is available so it is possible to compute a significant statistics for comparison reason. Moreover, we proposed a comparison on 99 real data from renal scintigraphy where relative renal functions are automatically computed and compared with those obtained by physician.
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Innovation Policy of Germany and its Impact on Balance of Trade
Tichý, Ondřej ; Gullová, Soňa (advisor) ; Klosová, Anna (referee)
This diploma thesis focuses on innovation policy of Germany, its development and characteristics. It briefly describes the state role in the area of innovation policy and authorities involved in there. This thesis deals with technological specialization in German innovation system and position of German research system in international comparison. It also analyzes the impact of innovation policy on balance of trade.
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Convolution Model of Time-activity Curves in Blind Source Separation
Tichý, Ondřej ; Šmídl, Václav
Availability of input and organ functions is a prerequisite for analysis of dynamic image sequences in scintigraphy and positron emission tomography (PET) via kinetic models. In PET, the input function can be directly measured by sampling the arterial blood. This invasive procedure can be substituted by extraction of the input function from the observed images. Standard procedure for the extraction is based on manual selection of a region of interest (ROI) which is user-dependent and inaccurate. The aim of our contribution is to demonstrate a new procedure for simultaneous estimation of the input and organ functions from the observed image sequence. We design a mathematical model that integrates all common assumption of the domain, including convolution of the input function and tissue-specific kernels. The input function as well as the kernel parameters are considered to be unknown. They are estimated from the observed images using the Variational Bayes method.
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Automated Functional Analysis in Dynamic Medical Imaging
Tichý, Ondřej
Dynamic medical imaging is concerned with acquisition and analysis of a sequence of images of the same region of a body during time. In nuclear medicine, each pixel of an image is the sum of particles coming from an applied radioactive tracer from the body in a specific time-interval. Hence, each observed image is a superposition of an unknown number of underlaying organ images. The aim of functional analysis is to separate the images of biologic organs and related time-activity curves from the sequence of images.
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Model Consideration for Blind Source Separation of Medical Image Sequences
Tichý, Ondřej
The problem of functional analysis of medical image sequences is studied. The obtained images are assumed to be a superposition of images of underlying biological organs. This is commonly modeled as a Factor Analysis (FA) model. However, this model alone allows for biologically impossible solutions. Therefore, we seek additional biologically motivated assumptions that can be incorporated into the model to yield better solutions. In this paper, we review additional assumptions such as convolution of time activity, regions of interest selection, and noise analysis. All these assumptions can be incorporated into the FA model and their parameters estimated by the Variation Bayes estimation procedure. We compare these assumptions and discuss their influence on the resulting decomposition from diagnostic point of view. The algorithms are tested and demonstrated on real data from renal scintigraphy; however, the methodology can be used in any other imaging modality.
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Variational Bayes in Distributed Fully Probabilistic Decision Making
Šmídl, Václav ; Tichý, Ondřej
We are concerned with design of decentralized control strategy for stochastic systems with global performance measure. It is possible to design optimal centralized control strategy, which often cannot be used in distributed way. The distributed strategy then has to be suboptimal (imperfect) in some sense. In this paper, we propose to optimize the centralized control strategy under the restriction of conditional independence of control inputs of distinct decision makers. Under this optimization, the main theorem for the Fully Probabilistic Design is closely related to that of the well known Variational Bayes estimation method. The resulting algorithm then requires communication between individual decision makers in the form of functions expressing moments of conditional probability densities. This contrasts to the classical Variational Bayes method where the moments are typically numerical.
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Factor Analysis of Scintigraphic Image Sequences with Integrated Probabilistic Mask of Factor Images
Tichý, Ondřej
Factor analysis is a well established mathematical method for factor separation in the analysis of scintigraphical sequences. The results are typically an input to the next step, e.g. factor analysis for computing significant diagnostic coefficients. However, this computing highly depends on proper identification of factors and their biological meaning, which is not ensure only by factor analysis. The main issue is separation overlaping factors from themselves and from tissue background covering the whole sequence. Factor analysis highly depends on prior information which allows us to set biologically reasonable conditions to a mathematical model. In this paper, we propose a mathematical model which estimates the probability mask of each image factor and sets it as a prior information for the next step of iterative algorithm based on Variational Bayes method. The new proposed model provides more realistic estimates of factors than the standard factor analysis.
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Set of metrics for e-shop Internet Mall, a.s.
Tichý, Ondřej ; Novotný, Ota (advisor) ; Táborský, Michal (referee)
Goal of diploma thesis is to develop set of metrics for Internet Mall, a.s. company, carrying business in online shopping. Secondary goal is practical demonstration of Business Intelligence (BI) analysis on selected metrics. Balanced scorecard (BSC), strategic planning and management system, was selected as a framework for model of metrics. Basic concept of BSC was upgraded by an e-commerce extension. These extensions appear to be mostly inspiration. Main sources of information were consultations with company`s representatives. Developing process for model of metric consist of several steps: 1. Definition of mission, vision and strategy 2. Creating strategic objectives for each BSC perspective 3. Defining connections among objectives in explicit cause-and-effect relationship 4. Assigning each objective one or more indicators 5. Accomplished Model of metrics 6. Practical demonstration of BI analysis on selected metrics Goal of practice part was fulfilled by simple implementation of BI analysis, using three selected metrics. The aim was on introducing analytics reports for management and explaining their features and benefits. Contribution of whole effort is in increasing of quality of decision making process (carrying by head executives) supported by analytics reports.
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Comparative standing of Bavaria in Germany
Tichý, Ondřej ; Steinmetzová, Dana (advisor) ; Hnát, Pavel (referee)
This bachelor thesis focuses on economic situation of Germany and its largest state Bavaria. It briefly describes Bavaria's historical evolution and its political system. This thesis deals with foreign trade emphasising on export. It is also related to state intervention supporting export during economic crisis and comparison with measures adopted in the Czech Republic.
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