Topic for state exam - program Medical electronics and bioinformatics

The student will answer three main questions, determined by the state exam committee  from the list of topics below. Complementary questions may be asked if necessary.

Common part:

  1. Statistical data analysis (BE4M36SAN)
    linear regression (assumptions, parameter estimates, model interpretation, feature selection/regularization, statistical comparison between different models), non-linear regression (examples of algorithms and their comparison), analysis of variance, linear and non-linear dimension reduction methods (requirements, examples of algorithms and their comparison), clustering (goals, formal task definition, complexity, examples of hierarchical and non-hierarchical clustering methods, spectral clustering), robust statistics (motivation for robust methods and their examples)
  2. Medical instrumentation and devices (BAM31LET)
    biomedical signal acquisition, electrodes, functional blocks of medical devices, typical circuits for realization of medical devices and parameters of medical devices, electrocardiography, measurement of cardiac output, blood pressure, haemodynamic parameters, pacemakers and defibrillators, electroencephalography, electromyography, spirometry, body temperature measurement
  3. Biological signals (BAM31BSG)
    signals of nerves, muscles, heart, brain, eyes, stomach, voice and speech. Genesis, acquisition, waveforms, parameters. Time and frequency domain analysis and processing, filtering, noise and artifact suppression, graphoelements detection. Spontaneous and evoked signals, subjective and objective evaluation of disorders, examples of pathologies. Polysomnography (sleep cycles), lung function (volumes, capacities).
  4. Medical imaging systems - optical, fluorescence and electron microscopy, principles and applications; X-rays - principles, sources and detectors; computed tomography (CT) - principles, construction, reconstruction techniques and applications; medical ultrasound - principles, generation, detection, Doppler and 3D ultrasound, contrast agents, applications; magnetic resonance imaging (MRI) - principles, spatial encoding and k-space, applications, functional MRI; nuclear imaging methods (SPECT, PET) - principles, reconstruction algorithms, applications; radiation safety limits. (BAM33ZSL)

Specialization Bioinformatics:

  1. Bioinformatics - biological sequence analysis (in particular, sequencing and sequence assembly, sequence alignment, (statistical) sequence modeling, phylogenetic trees; definition of the individual tasks, their complexity, algorithms and their typical use), modeling of higher structure of nucleic acids and proteins (levels of structure description, basic approaches to structure prediction), genomic databases and their use (DNA, RNA, and protein databases, gene expression, annotation databases, interaction databases). (BEAM36BIN)
  2. Combinatorial optimization - common combinatorial optimization problems including description of their application, problem formulation, complexity analysis and algorithms, integer linear programming, flows and cuts, shortest paths, travelling salesman problem, knapsack problem and scheduling. (BE4M35KO)
  3. Molecular biology and genetics - chemical composition of living matter, experimental models and methods, genetic code, structure of DNA, RNA and proteins, genome sequencing. (BE4M36MBG)
  4. Advanced algorithms  - standard graph algorithms with polynomial complexity, combinatorial algorithms and algorithms falling to algorithmic number theory -  isomorphism, primality and pseudorandom numbers, search trees and heaps, search in higher dimensions, exact and approximate text search using finite automata. (B4M33PAL)
  5. Statistical machine learning - empirical risk minimization and generalization error estimate, maximum likelihood estimation, EM algorithm, standard and deep neural networks and their learning algorithms, structured output models, Markov models, HMM, Bayesian learning and ensemble learning. (BE4M33SSU)

Specialization Medical electronics:

  1. Applications of electromagnetic fields in medicine - interaction of non-ionizing electromagnetic (EM) field with biological systems. Application of thermal effects of EM field in medicine - diathermy for physiotherapy, hyperthermia for oncology and ablation for cardiology and urology. Applicators for EM thermotherapy. Treatment planning using the patient's dielectric model. Perspective diagnostic methods based on microwave technologies - microwave differential tomography. Non-invasive temperature measurement inside human body by microwave radiometers.. (BAM17EPM)
  2. Physics for diagnostics and therapy - basic overview of biological effects of the electromagnetic field and their use in medicine - radiotherapy, computing systems for radiotherapy planning, radiotherapeutic simulators. Physical therapy - basic effects, indications and contraindications, electrotherapy, ultrasound therapy, magnetotherapy, phototherapy. Prosthetics - block diagrams, engines used in upper limb prosthesis. (A6M02FPT)
  3. Construction of medical systems - general structure of medical electronic instrument with analogue and digital part, measurement amplifiers, analog and switched-capacitor filters, measurement converters, A/D and D/A converters. Systems for computer aided design of measurement instruments, virtual medical measurement instruments (A6M38KLS)
  4. Neurophysiology - structure of neuron, glia, resting membrane potential, action potential in nerve cell, propagation of action potential, myelin, synapse, neurotransmitters, synaptic receptors, reflex, muscle spindle, spinal cord function, voluntarily movement control, role of basal ganglia and cerebellum in motor control, EEG and evoked potentials, sleep and wakefulness, types of memory and mechanisms of memory formation, pain and sensation, vision, hearing, conversion of sound waves to electrical signals, vascular supply to the brain. (BAM31NPG)
  5. Analog Signal Processing - basic transistor structures of analog electronic circuits, implementation of operational amplifier at transistor level: schematic diagram, function description, analysis. Synthesis of analog filters: properties of individual approximations in frequency and time domain, possibilities of realization including switched circuits and their properties. (B2M31ZAS)

Specialization Image processing:

  1. Combinatorial optimization - common combinatorial optimization problems including description of their application, problem formulation, complexity analysis and algorithms, integer linear programming, flows and cuts, shortest paths, travelling salesman problem, knapsack problem and scheduling. (BE4M35KO)
  2. Computer vision methods - Interest point detection. Correspondences between images. Detection of geometrical primitives. RANSAC. Searching in large image databases. Object tracking. (B4M33MPV)
  3. Advanced algorithms  - standard graph algorithms with polynomial complexity, combinatorial algorithms and algorithms falling to algorithmic number theory -  isomorphism, primality and pseudorandom numbers, search trees and heaps, search in higher dimensions, exact and approximate text search using finite automata. (B4M33PAL)
  4. Statistical machine learning - empirical risk minimization and generalization error estimate, maximum likelihood estimation, EM algorithm, standard and deep neural networks and their learning algorithms, structured output models, Markov models, HMM, Bayesian learning and ensemble learning. (BE4M33SSU)
  5. Medical image processing - preprocessing, linear and non-linear filtering, texture and texture descriptors, wavelets, compressed acquisition. Active contour segmentation, level sets, features, shape and appearance models, shape description and analysis. Non-linear registration, keypoints, similarity-based and multimodal registration. Advanced tomographic reconstruction. 3D visualization of shapes and surfaces. (BAM33ZMO)

Specialization Signal processing:

  1. Adaptive signal processing - Definition of adaptive system and basic terms. Typical adaptive filtering tasks. Convergence behavior of adaptive LMS algorithm and its modifications and RLS algorithm. Applications of adaptive filtering. Kalman filtering and its generalization. Decorrelation and separation of multidimensional signals. Beamforming, conditions, uniform linear array of sensors, simple method of determining the direction of signal arrival using data matrix, principles and properties of beamforming systems. (BE2M31ADA)
  2. Modeling and analysis of brain activity - example generative models of neural activity (membrane dynamics, single neuron models, population models). Specific challenges in analysing functional magnetic resonance imaging and electrophysiological signal. Functional and effective connectivity - definition, methods, relative advantages and disadvantages. Advanced topics in neuroimaging data analysis - statistical inference, dimension reduction,  surrogate models, graph theory. (BAM31MOA)
  3. Neurophysiology - structure of neuron, glia, resting membrane potential, action potential in nerve cell, propagation of action potential, myelin, synapse, neurotransmitters, synaptic receptors, reflex, muscle spindle, spinal cord function, voluntarily movement control, role of basal ganglia and cerebellum in motor control, EEG and evoked potentials, sleep and wakefulness, types of memory and mechanisms of memory formation, pain and sensation, vision, hearing, conversion of sound waves to electrical signals, vascular supply to the brain. (BAM31NPG)
  4. Advanced digital signal processing - Signal modelling, AR, MA, and ARMA processes. Time delay estimation of two sensor signals. Coherence function, MSC and its use, MSC estimation. Effect of noise on MSC estimation. Cepstral analysis. Definition of spectral and cepstral measures. Discrete cosine transform, Karhunen-Loeve transform and principal components analysis. Models of signal distortion. Simple inverse filtration. Wiener filtering. Principle of blind separation and blind deconvolution of signals. Wavelet transform and its use for noise reduction. Principles of sparse signal processing (compressed sensing) methods. (BE2M31DSP)
  5. Analog Signal Processing - basic transistor structures of analog electronic circuits, implementation of operational amplifier at transistor level: schematic diagram, function description, analysis. Synthesis of analog filters: properties of individual approximations in frequency and time domain, possibilities of realization including switched circuits and their properties. (B2M31ZAS)
Responsible person: prof. Ing. Jiří Jakovenko, Ph.D.