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Comparison of physiological parameter data generated by the Metalyzer 3B in the laboratory and the Metamax 3B for use in field research
Kříž, Tomáš ; Nohel, Michal (referee) ; Chlíbková, Daniela (advisor)
Increasing quality of the sport performance creates demands related to sports data acquisition which occurs in the natural environment. Such demands are then placed on the equipment manufacturers which need to adapt and adjust equipment for artificial as well as the outdoor environment. Furthermore, required equipment must be substantially reduced in terms of its weight as well as the size to minimize possible interference with the outdoor conditions. The remaining question is to which extent such adjustments influence the validity of the data inquiry and whether laboratory testing should be prioritized before outdoor testing. This thesis aims to provide a comparison between two oxygen consumption analysers across the unified evidence-based testing protocol. The first half of the testing is made with Metalyzer 3B (laboratory-based equipment), and the second part of the testing is made with Metamax 3B (outdoor-oriented equipment). Both analysers are produced by the Cortex company. The theoretical part of this project introduces the underlying theory of the oxygen consumption analysers and presents various methods used for the establishment of the VO2max. The practical part includes the measurements of set parameters on both devices with an identical test protocol. The t-test was used to prove statistical significance between Metamax 3B and Metalyzer 3B. Results of statistical analysis (V'O2 p = 0,54; V'CO2 p = 0,087; SF p = 0,49; V'E p = 0,2; DF p = 0,28; time p = 0,59) within the range of 95% confidence intervals.
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Validity of the VO2 Master Pro device for maximal oxygen consumption prediction and the measurement of resting metabolism
Goldschmidt, Tobiáš ; Nohel, Michal (referee) ; Chlíbková, Daniela (advisor)
Measurements of maximal oxygen uptake and resting metabolic rate are one of the most important things in testing athletes and madical patients. For these measurements are used breath analyzers. These analyzers are usually non-portable costly devices. VO2 Master Pro is on the other hand portable breath analyzer with much lower prize. It is biggest disadvantage is that it contains only O2 sensor and not CO2 sensor as madically aproved devices. Aim of this study is to determinate validity and difference of measurements between VO2 Master Pro and reference device for measuring maximal oxygen uptake and resting metabolic rate. Difference for measuring maximal oxygen uptake was 4,15 ± 4,41 %. For measuring of resting metabolic rate difference was 41,20 ± 11,44 %. For measuring of maximal oxygen uptake is VO2 Master Pro valid but for measuring of resting metabolic rate it is not. It was also confirmed, that size of measured value have non-linear corelation with size of difference in measuring maximal oxygen uptake.
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Time development analysis of treated lesion in spinal CT data
Nohel, Michal ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This diploma thesis is focused on time-development analysis of treated lesion in CT data. The theoretical part of the thesis deals with the anatomy, physiology, and pathophysiology of the spine and vertebral bodies. It further describes diagnostic and therapeutic options for the detection and treatment of spinal lesions. It contains an overview of the current state of usage of time-development analysis in oncology. The problems of the available databases are discussed and new databases are created for subsequent analysis. Futhermore, the methodology of time-development analysis according to the shape characterization and the size of the vertebral involvement is proposed. The proposed methodological approaches to feature extraction are applied to the created databases. Their choice and suitability is discussed, including their potential for possible usege in clinical practice of monitoring the development and derivation of characteristic dependences of features on the patient's prognosis.
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Image filtration effect on quality of subtractive angiography-based CT brain images of blood-vessels
Šipula, Samuel ; Nohel, Michal (referee) ; Chmelík, Jiří (advisor)
The aim of the bachelor thesis is to design filtering methods for the resulting quality of digital subtraction angiography. The role of filtration in this case is to suppress noise and strong structures to enhance vessel anatomy. Real patient data obtained using a computed tomography system are available for this purpose. In this work, the emphasis is mainly on noise suppression. Individual filtration techniques were implemented in MATLAB. The work further acquaints the reader with the theory of vascular supply to the brain, its imaging methods and the description of filters as discrete operators.
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EKG synchonization of electroporation pulses
Nohel, Michal ; Mézl, Martin (referee) ; Novotná, Veronika (advisor)
Bachelor thesis is focused on cells electroporation principle and its types. It further describes thermal and nonthermal ablation techniques with an emphasis on irreversible electroporation. It contains an overview of fields, where medical procedures in combination with ECG signal are used, and an overview of techniques and measurements of the electrocardiographic signal. Further, the sensitivity of the human body to electroporation pulses is discussed. During electroporation, short high-voltage pulses are applied. Ventricular fibrillation may occur if the electroporation pulse is applied to the vulnerable period of the heart rhythm. Synchronization of pulse application with heart activity of the patient is necessary for health and safety reasons in clinical practice. The practical part of the thesis is about a LabVIEW program for this kind of synchronization. The created program is tested and the obtained results achieved are evaluated in terms of practical use.
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Prediction of radiotherapy response in rectal cancer by MR
Chmela, Radek ; Nohel, Michal (referee) ; Mézl, Martin (advisor)
This diploma thesis deals with the issue of predicting the response of rectal cancer to radiotherapy. The work is divided into four chapters. In the first two, the anatomy of the rectum, types of cancer and individual diagnostic methods are described, together with algorithms for detecting objects in images. In the third chapter, there is a description of the solution for automatic segmentation and prediction of the effectiveness of radiotherapy. In the fourth chapter, the achieved results are discussed.
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Implementation of a deep learning model for vertebral segmentation in CT data
Blažkova, Lenka ; Nohel, Michal
This paper deals with the problem of vertebral segmentationin CT data with the use of deep learning approaches.Automatic segmentation of vertebrae is a very complex issueand would simplify the work of radiologists and doctors. Thepaper is focused on one of the models published and submittedto the Large Scale Vertebrae Segmentation Challenge (VerSe) in2020 from C. Payer et al. – Improving Coarse to Fine VertebraeLocalisation and Segmentation with SpatialConfiguration-Netand U-Net and its implementation and modification. The modelis evaluated on the corresponding public and hidden dataset. Itsmodification shows an improvement of the results in comparisonwith the published results, a mean Dice score improved from0.9165 to 0.9302 on the public dataset and from 0.8971 to 0.9264on the hidden dataset.
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Implementation of a deep learning model for vertebral segmentation in CT data
Blažková, Lenka ; Chmelík, Jiří (referee) ; Nohel, Michal (advisor)
This bachelor’s thesis deals with the problem of vertebrae segmentation in CT data with the use of deep learning. Firstly, there is a theoretical review focused on the anatomy and the pathologies of the spine and the vertebrae, the CT systems, and the deep learning models for vertebrae segmentation in 3D data. The following section contains a more detailed description of the chosen model. The fifth section describes the implementation of the chosen model and the proposed modification, together with the results on the relevant database. In the end, the model with the modification is used on the clinical data provided by the supervisor and its evaluation is described.
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Optic nerve head segmentation in retinal image data
Nohel, Michal ; Drahanský, Martin (referee) ; Kolář, Radim (advisor)
This diploma thesis deals with the segmentation of the optic disc and cup in retinal image data. The theoretical part of the thesis describes the optic disc and cup and provides an overview of the current state of the art in using machine learning methods for their segmentation. Furthermore, the basic principles and blocks of convolutional neural networks are described. Convolutional neural networks U-Net and its modification nnU-Net were trained on the created databases. These models were tested and the results obtained were discussed and compared with selected published methods. Finally, the models were evaluated in terms of their potential for practical application.
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Prediction of radiotherapy response in rectal cancer by MR
Chmela, Radek ; Nohel, Michal (referee) ; Mézl, Martin (advisor)
This diploma thesis deals with the issue of predicting the response of rectal cancer to radiotherapy. The work is divided into four chapters. In the first two, the anatomy of the rectum, types of cancer and individual diagnostic methods are described, together with algorithms for detecting objects in images. In the third chapter, there is a description of the solution for automatic segmentation and prediction of the effectiveness of radiotherapy. In the fourth chapter, the achieved results are discussed.
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