|
|
Texture analysis
Opletal, Tomáš ; Kratochvíla, Lukáš (referee) ; Honec, Peter (advisor)
Diploma thesis discusses texture analysis. Goal is to detect anomalies on the material, which could arise during process of making calenders on the nonwoven material. This thesis is using methods of Fourier transform with statistics and Neural networks to detect position of the missing calender.
|
|
|
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.
|
|
|
Quantification of fabrics and magmatic textures of rhyolite extrusive domes
Hrudková, Kristýna ; Lexa, Ondrej (advisor) ; Závada, Prokop (referee)
Bubbles in rhyolites are being formed during ascension of rhyolite magma up to the surface. That is beacuse of decreasing content of dissolved water in melt. Stability of bubbles is kept constant because of their own internal pressure, which they are able to sustain for a long period. Some bubbles can occure after the fragmentation of magma in extrusive bodies on the surface. Bubbles created this way have very small size and they don't participate in fragmentation. In my thesis I'm dealing with internal structure of some rhyolite magmatic bodies and description of mechanisms of bubble formation. Furthermore I will concentrate on methods of quantification of the internal structure of extrusive domes, i.e. the AMS magnetic minerals population structure and texture analysis of rock incisions. Texture analysis was concentrated on some aspects, which could help us to assess the extent of distribution of bubbles in strips. In conclusion, I compare the results of these methods to evaluate the importance of individual structural elements for structural-geological interpretation. We investigated samples from extrusive rhyolite body, which are being formed during the gradual egression of magma on the surface. We were investigated bubbles and their realtions between each other by using several methods. On the...
|
|
|
Texture analysis of tumor tissue in lung CT data.
Šalplachta, Jakub ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
The aim of this work is the revelation of the possibility of the use of texture analysis methods to detection and segmentation tumor tissue in lung CT image data and classification viable areas of tumor tissue. The main assumption of this thesis are differences of textural features between tumor and surrounding tissues and changes of these properties during development and treatment of this disease. The thesis contains overview of texture analysis methods. It deals with the creation of own method which is composed of some methods of texture analysis that create vector of properties (for each voxel in the image we get vector of features). This vector is afterwards processed by methods of cluster analysis. Content of this work is theoretical research of this issue, description of own method and statistical evaluation of the results. The method is processed in programming environment Matlab®.
|
|
|
Analysis of retinal nerve fiber layer in fundus images utilizing local binary patterns
Doležal, Petr ; Harabiš, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This work describes LBP (Local Binary Pattern) method in its various forms as a tool for distinguishing images with and without texture. The first part of the essay looks into the retinal nerve fiber layer, loss of the nerve fiber and especially into possibilities of retinal images with help of the fundus camera and into properties of this way received data. Second part of the essay describes and explains the LBP method which uses local binary operators for description of texture by help of histograms. From this way brought force of histograms is possible to gain a complex of features. Due to different classification approaches can then determine if new samples were selected from an image loss of retinal nerve fiber layer (RNFL). This solves the next part of the essay. And then is evaluated the correlation of features of LBP histograms of these images with the thickness of the RNFL in the same place. The methods described in this essay have been tested on a set of images in Matlab program and received results show, that the method can be useful for the diagnosis of glaucoma diseases.
|
|
|
Extraction of texture features aimed to detect glaucoma defects
Daněk, Daniel ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with an automatic method of texture analysis using Markov random fields texture modeling. The main aim of this work is to find out relevant textural features, which can be used for appropriate classification of the degree of retinal nerve fiber layer loss. The model of Markovian statistic uses a circular symmetric neighborhood structure and a least square error estimation of the model's parameter. Obtained textural features were quantitatively evaluated using correlation analysis. The results show, that there is a significant correlation between proposed textural features and RNFL thickness measured by OCT. Thus, the features can potentially serve for glaucoma diagnosis.
|
|
|
Intelligent features classification aimed to support diagnosis of glaucoma
Vykoupil, Pavel ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis deals with inteligent features classification aimed to support diagnosis of glaucoma. First part focuses on eye anatomy and disease called glaucoma. In next part is briefly described texture analysis and how do we get attributes for classification. In last part it is dealt with attribute classification with the aid of neural networks and algorithm HoKashyap and AdaBoost. This thesis is therefore focused on comparing effectivity of these classifiers on the field of optical diagnostics which was managed successfully.
|
|
|
Analysis of Ophthalmological Images Aimed to Diagnosis of Glaucoma
Vodáková, Martina ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Bachelor thesis is focused on fundamental texture analysis of high-resolution fundus images aimed to subjectively and quantitatively describe properties of texture formed by the retinal nerve fiber layer. An area of interest was predefined in the form of ten sectors on each fundus image. The correlation between results of subjective and quantitative evaluation of the texture was monitored in each sector. The results show that proposed fundamental texture features are closely related to the subjective textural properties obtained from visual appearance of the retinal nerve fiber layer. The last step compares results from fundamental texture analysis with quantitative measurement of the retinal nerve fiber layer thickness provided by Optical Coherence Tomography.
|
|
|
Smoke and Fire Detection in Video Sequences
Havelka, Robert ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
This master's thesis deals with fire detection in videosequences. Attention is paid to the known characteristics of fire and basic principles of existing solutions which deal with this issue. The thesis also describes design, implementation and testing of a fire detector that is based on the recognition of suspicious areas by fire color modeling, combined with detection of motion and light intensity variations.
|
|
|
Analysis of Retinal Image Data to Support Glaucoma Diagnosis
Odstrčilík, Jan ; Kybic, Jan (referee) ; Matula,, Petr (referee) ; Kolář, Radim (advisor)
Fundus kamera je široce dostupné zobrazovací zařízení, které umožňuje relativně rychlé a nenákladné vyšetření zadního segmentu oka – sítnice. Z těchto důvodů se mnoho výzkumných pracovišť zaměřuje právě na vývoj automatických metod diagnostiky nemocí sítnice s využitím fundus fotografií. Tato dizertační práce analyzuje současný stav vědeckého poznání v oblasti diagnostiky glaukomu s využitím fundus kamery a navrhuje novou metodiku hodnocení vrstvy nervových vláken (VNV) na sítnici pomocí texturní analýzy. Spolu s touto metodikou je navržena metoda segmentace cévního řečiště sítnice, jakožto další hodnotný příspěvek k současnému stavu řešené problematiky. Segmentace cévního řečiště rovněž slouží jako nezbytný krok předcházející analýzu VNV. Vedle toho práce publikuje novou volně dostupnou databázi snímků sítnice se zlatými standardy pro účely hodnocení automatických metod segmentace cévního řečiště.
|
guest ::
