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Segmentation of soft tissues in facial part of mouse embryos from X-ray computed microtomography data
Janštová, Michaela ; Harabiš, Vratislav (referee) ; Chmelík, Jiří (advisor)
This diploma thesis deals with a segmentation of soft tissues in facial part of mouse embryos in Matlab. Segmentation of soft tissues of mouse embryos was not fully automated and every case needs a specific solution. Solving parts of this issues can provide valuable data for evolutionary biologists. Issues about staining and segmentation techniques are described. On the basis of accessible literature otsu thresholding, region growing, k-means clustering and segmentation with atlas were tested. In the end of this paper are those methods tested and evaluated on 3D microtomography data.
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Computed tomography system with strict real-time synchronization for in-situ 3D analysis of periodically vibrating objects
Rada, Václav ; Fíla, Tomáš ; Zlámal, Petr ; Koudelka_ml., Petr ; Šleichrt, Jan ; Macháček, Michael ; Vavřík, Daniel ; Kytýř, Daniel
In the contribution, we present a laboratory system capable of X-ray computed tomography (XCT) scanning of an periodically moving or oscillating object. The system is an in-house developed XCT setup with electromagnetic voice coil actuator mounted on top of the rotary stage of the setup. The strict synchronization of the components, the rotary stage, the electromagnetic actuator movement and the detector readout is accomplished with use of the detector hardware trigger and hard real-time Linux operating system. Cylindrical sample manufactured from epoxy resin with metal particles to enable movement tracking is scanned in a stationary position and during periodical movement induced by the vibration stage. The volumetric data of the scans is compared and the results of this contribution represent an important step towards identification of defects through modal analysis of in-situ harmonically vibrating object.
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CT and MR and their mutual use in diagnostics
KOCHWASSER, Jiří
This bachelor thesis deals with computed tomography and magnetic resonance imaging and their mutual use in diagnostics. Computed tomography and magnetic resonance imaging are an integral part of modern radiology and play an essential role in the accurate diagnosis of many diseases. In this field, quality and modern instrumentation and a professional approach of the medical staff performing the examinations are important. In the first, theoretical part, the physical principles of computed tomography and magnetic resonance imaging, their history and their characterictis are described in detail. The theoretical part is compiled from the specialised literature, both printed and published on the Internet and is prepared in the form of a search. This thesis aims to describe the detailed physical principles of both diagnostic methods, to analyse the applicability of these imaging methods in hospitals and to analyse the mutual use of computed tomography and magnetic resonance imaging. The thesis is designed as a comrehensive review concerning the use and operations of CT and MRI imaging methods. To meet the objectives and research questions, we used annual reports, from 2012 to 2021, on the instrumentation of healthcare facilities from the Institute of Health Information and Statics of the Czech Republic (IHIS), which are provided under the Ministry of Health´s Statistical Survey Programme. This objective was supported by the research question: What is the most common use of CT and MRI in the algorithm of medical imaging examinations?
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Optimization of X-ray computed tomography method for imaging of low-density materials
Maleček, Lukáš ; Oberta, Peter (referee) ; Zikmund, Tomáš (advisor)
X-ray computed tomography is a technique enabling three-dimensional non-destructive imaging of the internal structure of measured objects. This imaging method has become a standard tool utilized in various fields, including medicine, industry, and science. Conventional X-ray computed tomography is based on the absorption of X-rays as it is passing through the measured object. However, this conventional imaging approach has its limitations, particularly when imaging objects with low density that causes only low X-ray attenuation. In such cases, sufficient contrast between the measured object and the background is not achieved. This thesis focuses on the optimization of phase contrast imaging, which utilizes phase changes of radiation as it is passing through the sample to overcome the limitations of absorption-based computed tomography. The detection of phase changes is achieved in the thesis using the propagation-based method. The main goal is to develop a methodology for finding the optimal parameters for the acquisition of tomographic data and also for the following processing of obtained X-ray projections. The results are qualitatively and quantitatively evaluated to assess the benefits of the developed methodology.
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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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Noise reduction in high resolution computed tomography data
Tkadlecová, Markéta ; Chmelík,, Jiří (referee) ; Zikmund, Tomáš (advisor)
Vzhledem ke komplexnosti procesu akvizice dat výpočetní tomografie (CT) je šum v rentgenových snímcích nevyhnutelný a může vést ke zkreslení získané informace. Proto by měl být co nejvíce potlačen. Dosud se výzkum zaměřoval především na redukci šumu v CT datech u lékařských CT s nízkými dávkami, zatímco o šumu a jeho potlačení v CT datech s vysokým rozlišením je známo jen málo. Tato redukce může probíhat v oblasti rentgenových snímků, v průběhu tomografické rekonstrukce nebo v oblasti tomografických řezů. Tato práce se zabývá především redukcí šumu v rentgenových snímcích a tomografických řezech. Prvním krokem k nalezení komplexní metodiky je určení rozdělení a matematického modelu šumu přítomného v rentgenových snímcích. Tento model byl určen pomocí snímků bez přítomného vzorku, které byly pořízeny s různými expozičními časy. Pomocí stanoveného modelu byl simulován šum ve fantomovém datasetu. Vybrané algoritmy byly testovány na projekčních snímcích a tomografických řezech fantomu a porovnávány jak subjektivně, tak objektivně pomocí metrik kvality obrazu. Strategie s nejlepšími výsledky byly dále testovány na naměřených CT datech z CT systému Rigaku nano3DX s vysokým rozlišením a byly popsány jejich výhody, omezení a možnosti využití.
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