The doctoral study provides the graduates of MSc study in the area of biomedical electronics and biocybernetics with a higher degree of education, deepening their theoretical background.
The study is aimed at deepening of theoretical knowledge of students in advanced mathematics, physics and in disciplins forming the theoretical basis of the chosen field. Also, necessary experience in experimental work and in processing of the obtained results should be provided, including exploitation of advanced methods of applied informatics.
The final goal is that the students will master methods of scientific research.

A graduate of the doctoral study is expected to be a distinct personality with a recognised research result, wide horizon of knowledge and ability to solve complex scientific and technical-research tasks in the field of biomedical electronics and biocybernetics and in neighbouring fields.
Maximum flexibility and professional adaptivity is the undisputed property of a graduate of doctoral study.
The graduates of the doctoral study in biomedical electronics and biocybernetics will be capable of working as scientists and researchers involved in basic or applied research namely in medical or biological area, as leading specialists in development and construction departments of research and development institutions, and in manufacturing enterprises or institutions exploiting advanced technology, namely in biomedical field.

Graduate of doctoral programme should be a strong personality with substantial scientific results, large horizon and ability to solve complex scientific and research technical tasks in area of biomedical electronics and biocybernetics. He/she will have maximum flexibility and professional adaptability in wide area of biomedical engineering. Graduates will be able to work as scientific and research staff in basic and applied research, as specialists in development, construction and production, in research institutes and at industrial companies and users of medical devices and applied information technologies in medicine and biology.

prof. Ing. Jiří Jan, CSc.

2. round (applications submitted from 04.07.2016 to 20.07.2016)

1. Analysis of 3D CT image data aimed at deformable model based segmentation of different types of skeletal elements

   Design and development of new methods of CT image data analysis, namely for reliable segmentation of different types of skeletal elements based on, aimed at different clinical applications (cooperation with international and regional medical institutions). The theme is a part of a long-term project supported by the firm PHILIPS NEDERLAND in frame of a contract, enabling to offer – to successful students – an interesting regular increase added to the stipend. The applicant is expected, besides of being interested in research work in a renowned team, to be capable of formulating structured algorithms, programming in MATLAB environment and mastering basic methodology of image processing and analysis.

   Tutor: Jan Jiří, prof. Ing., CSc.

2. Analysis of 3D CT image data aimed at following of temporal development of local bone mineral density

   Design and development of new methods for automatic detection of bone mineral density in CT scans aimed at different clinical applications, using advanced methods of tissue classification and possibly utilising results of previous research of the research group. The project is long-term supported by Philips Nederland, and medically cooperates with AKH Wien (Dr. med. M. Gruber) a Yinchuan Hospital (China). The applicant is expected to master basic methodology of image processing and analysis, and have good background in programming numerical methods in MATLAB utilizing also links to different programme libraries.

   Tutor: Jan Jiří, prof. Ing., CSc.

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. Quantitative Methods of Perfusion Imaging in Ultrasonography

   The project is a continuation of a longterm development of ultrasonography acquisition methods and the subsequent image data processing aimed at quantification of blood flow and volume in the imaged tissues. This project will include extension of the current bolus&burst method by blind-deconvolution algorithms, more realistic pharmacokinetic models, image registration, evaluation on simulated, preclinical and clinical data.

   Tutor: Jiřík Radovan, doc. Ing., Ph.D.

1. round (applications submitted from 01.04.2016 to 15.05.2016)

1. Advanced detection of fingerprint liveness in Biometrics

   The theme of this dissertation is aimed on software recognition of fingerprint liveness from image fingerprint data and it can be divided into two parts. The goal of the first part is to find features, which are suitable for detection of various types of false fingerprints. The goal of the second part is to design an advanced algorithm for recognition of false fingerprints from real ones regardless on type of false fingerprint, sensing device, or image data resolution. Applicants are expected to be familiar with Matlab programming and have an overview in the area of processing and analysis of image data.

   Tutor: Vítek Martin, Ing., Ph.D.

2. Analysis of Non-Stationary Cardiac Signals

   The project will be focused on processing of electrocardiograms (ECG) and heart rate variability (HRV) signals by use of empirical mode decomposition (EMD) and Hilbert-Huang transform. The analytical part of the project include a development of the new methods for automatic processing and analysis of human ECG signals and electrograms recorded from the hearts of experimental animals using the optical system at Medical Faculty of Masaryk University.

   Tutor: Kozumplík Jiří, doc. Ing., CSc.