prof. Ing. Valentine Provazník, Ph.D.

2. round (applications submitted from 03.07.2017 to 25.07.2017)

1. Advanced methods for ECG signal quality estimation

   The theme of this dissertation is aimed on continuous quality monitoring in long-term ECG records. The goal of the first part is to evaluate the quality of ECG signal recorded from different locations on the body using mobile recorder and possibilities of simultaneously recorded physical activity by gyroscope. The goal of the second part is to design advanced algorithms for continuous and real-time estimation of the ECG signal quality and subsequent identification of segments with the same quality. Applicants are expected to programming skills in Matlab and base knowledge of the processing and analysis of 1D signal.

   Tutor: Vítek Martin, Ing., Ph.D.

2. Deep learning methods for image data processing

   This topic deals with current variants of artificial neural networks in the areas of processing and analysis of still images and videosequences. It is expected that deeper study will be needed in the following areas: convolution neural networks, transfer learning for application in other tasks, progressive learning to solve new and complex problems and application of recurrent neural networks for segmentation and tracking objects in the image data. Specific applications will primarily focus on segmentation and tracking of people and objects in general scenes, including face detection with the use in biometrics and biomedicine.

   Tutor: Kolář Radim, doc. Ing., Ph.D.

3. Laser speckle contrast imaging

   The theme of this thesis is aimed on optical measurement of flow rate using image processing of speckles which are created using coherent light source. The main aim is the study and extension of this method using non-ideal optical medium and increasing the robustness of flow rate estimation. The method will be applicated especially in ophthalmology. Design and development of suitable flow phantoms of blood-vessels in the retina will be also part of this thesis. Advanced methods of image processing including segmentation, texture analysis and image acquisition will be used for the solution of this thesis. Overall, this project should be able to extend diagnosis potential of video-ophtalmoscopes of the eye and neurological diseases. This theme fits into a long-term cooperation with the clinical institute in Erlangen (Germany).

   Tutor: Harabiš Vratislav, Ing., Ph.D.

4. Tracking of transplanted cells - methods of labeling and detection of cells

   The thesis deals with the research methods of labeling and detecting cells, which are used in routine or experimental transplantation (mesenchymal stromal cells, dendritic cells, hematopoietic cell, chondroblasts). The trend in recent years is to label the cells by more independent labels or integrated multimodal labels including nanoparticles. Thesis summarizes current knowledge and compares different labels from point of view of combination of options, long-term detectability, stability in the cell, cell biocompatibility and possibilites of quantification of a set of cells in a unit volume of tissue. The work tests the possibility of cell labeling different by commercial and experimental labels, their biocompatibility and subsequent possibility to detect labeled cells and the detection limits of cells in both the idealized in-vitro conditions and in the model of the real tissue iand also in the real tissue. The results will be used in ongoing projects solving paramagnetic nanoparticle-based delivery of DNA plasmid, endothelial cell monolayer studies, and monitoring adherent regenerative cells and characterization of their migration.

   Tutor: Provazník Valentine, prof. Ing., Ph.D.

1. round (applications submitted from 01.04.2017 to 15.05.2017)

1. Analysis of gene expression in cardiomyopathy by bioinformatics methods

   Cardiomyopathy is a common cause of heart failure and cardiac transplantation. This study is aimed to explore potential cardiomyopathy-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles from Gene Expression Omnibus database will be used. The differentially expressed genes will be searched between normal and cardiomyopathy-related samples using new bioinformatics methods. Further, potential transcription factors and microRNAs of these cardiomyopathy-related genes will be predicted based on their binding sequences. In addition, cardiomyopathy-related genes will be used to find potential small molecule drugs as potential therapeutic drugs for cardiomyopathy.

   Tutor: Provazník Valentine, prof. Ing., Ph.D.

2. Effect of the hemodynamic processes on the electrical activity of the isolated heart

   The project deals with analysis of experimental cardiology data. The goal will be isolated hearts hemodynamic monitoring in relation to electrophysiological phenomena. The first part will be a detailed study of the electrophysiological and hemodynamic events in the heart during each cardiac phase. The second application part is focused on the design of advanced algorithms for pre-processing and analysis of simultaneously recorded signals. The goal of the work will be a description of dynamic processes during experiments focused on cardiac workload change studies. Databases of experimental data is available on Department of Biomedical Engineering.

   Tutor: Kolářová Jana, doc. Ing., Ph.D.