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Analysis of retinal nerve fiber layer for diagnosis of glaucoma
Vodáková, Martina ; Malínský, Miloš (referee) ; Odstrčilík, Jan (advisor)
The master thesis is focused on creating a methodology for quantification of the nerve fiber layer on photographs of the retina. The introductory part of the text presents a medical motivation of the thesis and mentions several studies dealing with this issue. Furthermore, the work describes available textural features and compares their ability to quantify the thickness of the nerve fiber layer. Based on the described knowledge, the methodology to make different regression models enabling prediction of the retinal nerve fiber layer thickness was developed. Then, the methodology was tested on the available image dataset. The results showed, that the outputs of regression models achieve a high correlation between the predicted output and the retinal nerve fiber layer thickness measured by optical coherence tomography. The conclusion discusses an usability of the applied solution.
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Segmentation in the color fundus imges
Malínský, Miloš ; Jiřík, Radovan (referee) ; Kolář, Radim (advisor)
Optic nerve head and macula are important structures in fundus images. Detection and measurement plays crucial role in several diagnosis methods of optic disease. This work is focused on the detection of the central point of macula and optic nerve head, where the inner border is detected too. There are many methods for extracting this structure in retinal images. Due to the unique properties of each acquisition technique, a single generally acknowledged detection algorithm does not exist. The whole detection process is described from preprocessing through segmentation towards postprocessing. Presented methods are based on the combination of correlation techniques, Hough transform, active contours and morphological operations. The detected contours of the optic nerve head are evaluated and quantitatively compared with the contour drawn by experienced ophthalmologist. The master thesis contains quantity of images that help to describe detection methods.
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Segmentation of the basic parts of human brain in MR data
Klásek, Pavel ; Jiřík, Radovan (referee) ; Malínský, Miloš (advisor)
This work describes segmentation methods used in image data processing, from which there are selected and implemented suitable methods for solving the assignment of segmentation parts of human brain – region growing and watershed algorithm. Segmentation techniques are realized on real data sources. Final segmentation results are presented, compared and evaluated accordig to the advanced software FreeSurfer segmentation results. In addition there is a list of available software that can be applied for the purpose of neurological image segmentation.
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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 3D CT image data aimed at detection and classification of specific tissue structures
Šalplachta, Jakub ; Malínský, Miloš (referee) ; Jan, Jiří (advisor)
This thesis deals with the segmentation and classification of paraspinal muscle and subcutaneous adipose tissue in 3D CT image data in order to use them subsequently as internal calibration phantoms to measure bone mineral density of a vertebrae. Chosen methods were tested and afterwards evaluated in terms of correctness of the classification and total functionality for subsequent BMD value calculation. Algorithms were tested in programming environment Matlab® on created patient database which contains lumbar spines of twelve patients. Following sections of this thesis contain theoretical research of the issue of measuring bone mineral density, segmentation and classification methods and description of practical part of this work.
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Movement correction in thoracic dynamic contrast CT data
Jakubíček, Roman ; Malínský, Miloš (referee) ; Walek, Petr (advisor)
This thesis deals with a nonrigid image registration for movement correction in thoracic dynamic contrast CT data. The deformation field is initialized by the analysis of disparities based on nonlinear matched filter, which defines local movement deformation. The values of control points are optimized by the Nelder-Mead method. The transformation model is based on a 4D (3D + time) free-form B-spline deformation for feature of movement distortion. The first part of the thesis briefly discusses the theory of image registration. Knowledge of this theory is necessary for understanding the remaining chapters, which describe the proposed method and its realization. The large part of this thesis is devoted to the geometrical image transformations, that is very important for the image registration. The thesis also describes a simplex method for function minimization. Three publicated methods of registration of medical 4D CT data are given. In the following chapter are individual parts of the purposed nonrigid registration including possible problems and their solution described.
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Feature tracking method for medical images registration
Jakubík, Tomáš ; Malínský, Miloš (referee) ; Harabiš, Vratislav (advisor)
The aim of this thesis is to familiarize with the issue of registration of medical image sequences. The main objective was to focus on the method of feature tracking in the image and various options of its implementation. The theoretical part describes various methods for detection of feature points and future point matching methods. In the practical part these methods were implemented in Matlab programming environment and a simple graphical user interface was created.
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Image registration using Optical Flow method
Bistrý, Jan ; Provazník, Ivo (referee) ; Malínský, Miloš (advisor)
Registration of medical images is technique, which is developing with new hybrid diagnostic imaging systems. Nowadays is a trend in image registration focused on monomodality and multimodality images registration. The first part of this master’s thesis is intent on present basic information about image registration. Concretely is intending on image transformation, interpolation, criteria function and at optimalization. Further part present realized Optical Flow technique and used “Demon” algorithm for image registration. The next part is focused on presentation of program solution and GUI. In the last section of this master’s thesis is verifying of created program on usual images and real CT images.
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CT X-ray quantitative evaluation
Novotný, Lukáš ; Malínský, Miloš (referee) ; Drastich, Aleš (advisor)
X-Ray Computed Tomography is irreplaceable medical imaging system. Quantitative evaluation is day to day routine used for clean run of this imaging system. The master’s thesis is focused on quantitative evaluation of first and third generation X-Ray CT. First of all is about subjective and objective evaluation of space and energetic resolution. Space resolution is evaluated in space and frequency domain. Energetic resolution is represent by low contrast resolution method. Application “Kvantitativní hodnocení kvality CT RTG zobrazení” created for this thesis is used for creation of reconstruction image and quantitative evaluation. This application was created with consideration of its usage in subjects about image processing. The master’s thesis contains results of quantitative evaluation X-Ray CT created with this application and proposal of lab work.
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