|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
Detection of the retinal nerve fibre layer
Kunc, Martin ; Szabó, Zoltán (referee) ; Kolář, Radim (advisor)
This thesis is deals with the nerve fibre layer in the colour ophthalmology images of retina. The thesis describes how can we use finding of nerve fibre layer and how was it solved in the past. In the thesis are proposed the methods that are based on processing and scoring frequency spectrums of individual sample of retina. At first here are described the methods of detection on the artificial generated samples that just simulate the nerve fibre layer. Then the thesis concentrates on processing of real images of retina. Because of the bloodstream, that depreciates processing at real images, are all surveyed samples are chosen manually. Except detection the nerve fibre layer itself, the thesis also deals with determination of direction their dissemination.
|
|
|
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.
|
|
|
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.
|
|
| |
|
|
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.
|
|
|
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.
|
|
| |
guest ::
