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Advanced methods for cardiac cells contour detection
Spíchalová, Barbora ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This thesis focuses on advanced methods of detecting contours of the cardiac cells and measuring their contraction. The theoretical section describes the types of confocal microscopes, which are used for capturing biological samples. The following chapter is devoted to the methods of cardiac cells segmentation, where we are introduced to the generally applied approaches. The most widely spread methods of segmentation are active contours and mathematical morphology, which are the crucial topics of this thesis. Thanks to the those methods we are able in the visual data to accurately detect required elements and measure their surface chnage in time. Acquired theoretical knowledge leads us to the practical realization of the methods in MATLAB.
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Software image processing of infrared thermograms of the lower limbs of diabetic patients
Langerová, Jana ; Mézl, Martin (referee) ; Bernard, Vladan (advisor)
This work deals with the automatic processing of the thermal images of the soles of the lower limbs. It contains general research in the topic of diabetic foot syndrome and general description of diabetes mellitus. It also deals with the theoretical area of the infrared radiation used in thermovision techniques and image processing techniques. In the second part, there is practically described the proposition of the software and then also its realization and commissioning. Created software contains two main possibilities for cropping the searching sole, the first one is completely manual detection and the second one is automatic with manual correction. In this work, there are also described all the procedures for reaching of the temperature analyzes. Last part of this work is dedicated to statical valorization of the information, which was got by the created software and which is conceived generally and serves to functional valorization of the created software.
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Segmentation of the kidney from the renal perfusion MR image sequences
Jína, Miroslav ; Walek, Petr (referee) ; Malínský, Miloš (advisor)
This master’s thesis deals with kidney segmentation in perfusion magnetic resonance image sequences. Kidney segmentation is carry out by a few methods such as regionbased techniques, deformable models, specimen-based methods, edge-oriented methods etc. The universal algorithm for patient kidney segmentation still does not exist. Proposed method is an active contour Snake, which is created in programming environment MatLab. Final contours are quantitatively and visually compared to manual kidney segmentation.
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Analysis of volumetric change of Hippocampus caused by Alzheimer's disease
Pham, Minh Tuan ; Harabiš, Vratislav (referee) ; Walek, Petr (advisor)
Interest in hippocampus increased sharply after his significance in the process of learning and retention of information was published. In particular, considerable interest was in its volume changes and their effect on Alzheimer’s disease. Understanding the structure and function hippocampus would contribute to a more accurate diagnosis of this disease. In this work was created a method of hippocampal segmentation using active contours. With its help, the data composed of both healthy and a diseased patients was segmented and the results were then statistically analyzed using statistical methods such as Kruskal-Walis test, Mann-Whitney test. The level of significance given by results of analysis supports alternative hypothesis that attaches significance of the difference in volume of the hippocampus between studied groups.
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Cell tracking in images from holographic microscope
Vičar, Tomáš ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
This thesis focuses on cell tracking in image sequences acquired using a multimodal holographic microscope (MHM). The principles of holographic microscopy are described together with the application in cells acquisition. The main part of the thesis describes a complete approach for segmentation and tracking of single cells in acquired in long-term sequences. The approach is designed based on parametric active contour models with specific modifications to achieve reasonable precision and robustness. The implemented method is described in detail, including the evaluation and demonstration of results.
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Computer Aided Recognization and Classification of Coat of Arms
Vídeňský, František ; Kočí, Radek (referee) ; Zbořil, František (advisor)
This master thesis describes the design and development of the system for detection and recognition of whole coat of arms as well as each heraldic parts. In the thesis are presented methods of computer vision for segmentation and detection of an object and selected methods that are the most suitable. Most of the heraldic parts are segmented using a convolution neural networks and the rest using active contours. The Histogram of the gradient method was selected for coats of arms detection in an image. For training and functionality verification is used my own data set. The resulting system can serve as an auxiliary tool used in auxiliary sciences of history.
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Segmentation Methods in Biomedical Image Processing
Mikulka, Jan ; Přibil, Jiří (referee) ; Dostál, Otto (referee) ; Gescheidtová, Eva (advisor)
The PhD thesis deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It is focused primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR) and microscopic images of tissues. It is easy to describe edges of the sought objects using of segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown in this thesis. Research in the area of image segmentation is focused on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions between objects. The results of the thesis are methods proposed for automatic image segmentation and classification.
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Segmentace mikroskopických snímků pomocí level-set metod
Bílková, Zuzana ; Kučera, Václav (advisor)
Název práce: Segmentace mikroskopických snímků pomocí level-set metod Autor: Zuzana Bílková Katedra: Katedra numerické matematiky Vedoucí diplomové práce: RNDr. Václav Kučera, Ph.D., KNM, MFF UK Konzultant: RNDr. Jindřich Soukup, ÚTIA, AV ČR Abstrakt: Tato diplomová práce představuje novou metodu pro segmentaci snímků pořízených mikroskopem s fázovým konrastem. Cílem je oddělit buňky od pozadí. Algoritmus je založen na variační formulaci level set metod, tedy na minimalizaci funkcionálu popisujícího level set funkci. Funkcionál je minimalizován gradientním tokem popsaným evoluční parciální diferenciální rovnicí. Nejdůležitější nové myšlenky jsou inicializace pomocí prahování a nové členy ve funkcionálu, které zrychlují konvergenci a zpřesňují výsledky. Také jsme použili nové funkce napsané v jazyce C k počítání gradientu a Laplaceova operátoru. Tato implementace je třikrát rychlejší než standardní funkce v MATLABu. Dosáhli jsme lepších výsledků než algoritmy, se kterými jsme metodu porovnávali. Klíčová slova: Segmentace, level set metody, aktivní kontury Title: Segmentation of microscopic images using level set methods Author: Zuzana Bílková Department: Department of Numerical Mathematics Supervisor: RNDr....
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Analýza zafarbených buniek
Hanzely, Tomáš
Hanzely, T. Analysis of colored cells. Bachelor thesis. Brno: Mendel University, 2018. The bachelor thesis aims to analyze colored cells, specifically cell quantification. Main goal is to create a cell counting application which is able to obtain cell counts for colored and uncolored cells and create graphic user interface for this application. Results are compared to ground truth and efficiency of the application is evaluated.
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Segmentace mikroskopických snímků pomocí level-set metod
Bílková, Zuzana ; Kučera, Václav (advisor)
Název práce: Segmentace mikroskopických snímků pomocí level-set metod Autor: Zuzana Bílková Katedra: Katedra numerické matematiky Vedoucí diplomové práce: RNDr. Václav Kučera, Ph.D., KNM, MFF UK Konzultant: RNDr. Jindřich Soukup, ÚTIA, AV ČR Abstrakt: Tato diplomová práce představuje novou metodu pro segmentaci snímků pořízených mikroskopem s fázovým konrastem. Cílem je oddělit buňky od pozadí. Algoritmus je založen na variační formulaci level set metod, tedy na minimalizaci funkcionálu popisujícího level set funkci. Funkcionál je minimalizován gradientním tokem popsaným evoluční parciální diferenciální rovnicí. Nejdůležitější nové myšlenky jsou inicializace pomocí prahování a nové členy ve funkcionálu, které zrychlují konvergenci a zpřesňují výsledky. Také jsme použili nové funkce napsané v jazyce C k počítání gradientu a Laplaceova operátoru. Tato implementace je třikrát rychlejší než standardní funkce v MATLABu. Dosáhli jsme lepších výsledků než algoritmy, se kterými jsme metodu porovnávali. Klíčová slova: Segmentace, level set metody, aktivní kontury Title: Segmentation of microscopic images using level set methods Author: Zuzana Bílková Department: Department of Numerical Mathematics Supervisor: RNDr....
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