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Advanced Algorithms for 3D Medical Image Data Fusion in Specific Medical Problems
Malínský, Miloš ; Flusser,, Jan (referee) ; Kozubek,, Michal (referee) ; Jan, Jiří (advisor)
Fúze obrazu je dnes jednou z nejběžnějších avšak stále velmi diskutovanou oblastí v lékařském zobrazování a hraje důležitou roli ve všech oblastech lékařské péče jako je diagnóza, léčba a chirurgie. V této dizertační práci jsou představeny tři projekty, které jsou velmi úzce spojeny s oblastí fúze medicínských dat. První projekt pojednává o 3D CT subtrakční angiografii dolních končetin. V práci je využito kombinace kontrastních a nekontrastních dat pro získání kompletního cévního stromu. Druhý projekt se zabývá fúzí DTI a T1 váhovaných MRI dat mozku. Cílem tohoto projektu je zkombinovat stukturální a funkční informace, které umožňují zlepšit znalosti konektivity v mozkové tkáni. Třetí projekt se zabývá metastázemi v CT časových datech páteře. Tento projekt je zaměřen na studium vývoje metastáz uvnitř obratlů ve fúzované časové řadě snímků. Tato dizertační práce představuje novou metodologii pro klasifikaci těchto metastáz. Všechny projekty zmíněné v této dizertační práci byly řešeny v rámci pracovní skupiny zabývající se analýzou lékařských dat, kterou vedl pan Prof. Jiří Jan. Tato dizertační práce obsahuje registrační část prvního a klasifikační část třetího projektu. Druhý projekt je představen kompletně. Další část prvního a třetího projektu, obsahující specifické předzpracování dat, jsou obsaženy v disertační práci mého kolegy Ing. Romana Petera.
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Texture Analysis of Ophthalmologic Images
Kaňka, Jan ; Odstrčilík, Jan (referee) ; Jan, Jiří (advisor)
This thesis is concerned with creating of software for textural analysis of retinal images by statistic method called co-occurrence matrices as possible alternative method to detection of lesion of retina by the glaucoma diseases. The Glaucoma diseases without well-timed diagnostics and consequential treatment leads to blindness. The retinal images captured by fundus camera are common, easily processable and modern devices are able to make images of 10 Mpix resolution and bigger, what specifies outputs of analytic software. Method of co-occurrence analysis is simple and effective statistic. But computing demandingness, showing up with growing objective quality, comming up as disadvantage.
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Segmentation of 3D image data using advanced textural and shape features
Novosadová, Michaela ; PhD, Miloš Malínský, (referee) ; Jan, Jiří (advisor)
This thesis first describes theory of range of methods of textural and shape analysis. In several published articles some of the mentioned methods are used for automatic detection of lesion in spine in CT images. Some of these articles are shortly presented (in this thesis). Next part of the thesis includes description of various classifiers which are used for classification of feature vectors. Practical part of the thesis is a design and implementation of image data segmentation solution (metastatic lesions in vertebrae) with use of classification of feature vectors formed by texture and shape symptoms. The thesis also deals with the selection of significant features for segmentation. Segmentation algorithm is tested on medical data.
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Analysis of Retinal Images Aimed to Nerve Fiber Layer Detection
Spáčil, Michal ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Goal of this work is to theoretically develop and then program a system in Matlab environment to be used as a detection tool for layer of retinal neuron pathways . First part engages oneself upon the problem of analysis within spectral plane and results of using filters conceived upon statistical occurrences of certain frequencies in used samples. Second part than deals with use of gabor filters to detect neuron pathways and the statistical results gained by their use. Based on the results an analysis tool was programmed.
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Texture analysis of retinal images
Mikauš, Jakub ; Odstrčilík, Jan (referee) ; Gazárek, Jiří (advisor)
The thesis deals with the detection of the nerve fiber layer disruptions in retina scans. The introduction presents an overview of the human eye fysiology and analyses the input image data. The thesis continues with an investigation of two texture analysis methods. While the method of adapted filters does not produce very good results, the method of brightness assessment is shown to work satisfactorily. The final part of the thesis describes the implemented tool for the detection of the nerve fiber layer disruptions.
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Textural Analysis of Nerve Fibre Layer in Retinal Images
Novotný, Adam ; Jan, Jiří (referee) ; Odstrčilík, Jan (advisor)
This work describes completely new approach to detection of retinal nerve fibre layer (RNFL) loss in colour fundus images. Such RNFL losses indicate eye glaucoma illness and an early diagnosis of RNFL changes is very important for successful treatment. Method is presented with the purpose of supporting glaucoma diagnosis in ophthalmology. The proposed textural analysis method utilizes local binary patterns (LBP). This approach is characterized especially by computational simplicity and insensitivity to monotonic changes of illumination. Image histograms of LBP distributions are used to gain several textural features aimed to classify healthy or glaucomatous tissue of the retina. The method was experimentally tested using fundus images of glaucomatous patients with focal RNFL loss. The results show that the proposed method can be used in order to supporting diagnosis of glaucoma with satisfactory efficiency.
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Texture analysis of retinal images oriented towards detection of neronal fibre layer
Gazárek, Jiří ; Jiřík, Radovan (referee) ; Jan, Jiří (advisor)
The thesis is focused on detection of local disappearance of the neural layer on retina in fundus-camera images. The first chapter describes the human eye physiology, the glaucoma disease and the analyzed data. The second chapter compares four different approaches that should enable automatic detection of a possible damage to the retinal neural layer. These four approaches have been tested and evaluated; three of them showed an acceptable correlation with the medical expert conclusions – the directional spectral approach, the edge based approach and the difference local brightness. The last approch via local co-occurrence matrices has not turned out to be informative with the respect to the issue concerned. Then a program for the automatic detection of the nerve fibre layer loss areas has been designed, realized and evaluated. This task is solved in the last chapter. A relatively good agreement between the medical expert conclusions and the conclusions detected automatically by this program has been reached.
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Methods for texture analysis in ophthalmologic images
Hanyášová, Lucie ; Szabó, Zoltán (referee) ; Kolář, Radim (advisor)
This thesis is focused on texture analysis methods. The project contains an overview of widely used methods. The main aim of the thesis is to develop a method for texture analysis of retinal images, which will be used for distinction of two patient groups, one with glaucoma eyes and one healthy. It is observed that glaucoma patients don´t have a texture on the eye ground. Preprocessing of the images is found by transfer of the image to different color spaces to achieve the best emphasis of the eye ground texture. Co-occurrence matrix is chosen for texture analysis of this data. The thesis contains detail description of the chosen solutions and feature discussion and the result is a list of features, which can be used for distinction between glaucoma and healthy eyes. The method is implemented in Matlab environment.
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Detection of the nerve fibres in ophthalmologic images
Urbánek, Dušan ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
This thesis deals with detection of the retinal nerve fiber layer in gray level retinal images taken by fundus camera. The first part describes a physiology of human eye and glaucoma disease. Then, the use of wavelet transform and algorithm of texture analysis applied for texture analysis. Next chapters describe theory of texture analysis named „Gray level run length matrices“ and its application for detection of the nerve fiber layer. Applications of this method are described for three types of retinal tissues and for whole image. The last chapter describes gray levels around optic disc and results obtained from parameters from GLRL matrices.
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