|
|
Preprocessing of retinal images aimed at support diagnosis of glaucoma
Holásková, Anna ; Walek, Petr (referee) ; Odstrčilík, Jan (advisor)
Preprocessing of retinal images can serve as a first phase of the further image analysis or the first step preceding diagnosing of various eye diseases. The preprocessing thus represents methods of image adjustments that can improve visual characteristics of fundus images. These methods mainly include the removal of noise generated during data acquisition, contrast and brightness transformations, edge detection and thresholding. This work handles with the basic methods of image preprocessing and specific methods of preprocessing of retinal images. The preprocessing includes global illumination correction, high-pass and homomorphic filtering and adaptive enhancement of the images. Manual methods for fundus image preprocessing that are usually based on the doctor's experience can be used as well. Hence, a procedure for enhancement of retinal images using Adobe Photoshop is mentioned in this work too. Three methods for preprocessing of fundus images were selected and implemented in MATLAB programming software. These methods include homomorphic filtering, CLAHE (Contrast Limited Adaptive Histogram Equalization) and adaptive enhancement. Experimental program functions were created and tested on the available image data. Results of the selected methods are mentioned in the conclusion section. Instructions for use of implemented functions are in appendix.
|
|
|
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.
|
|
|
Criterial function for retinal image registration
Horáková, Pavla ; Kolář, Radim (referee) ; Harabiš, Vratislav (advisor)
This bachelor‘s thesis is focused on comparison criterial functions, which are usually used in registration of retinal images. Criterial functions reflect degree of images’ sameness thereby they influence proper registration considerably. The aim of this thesis is to discover criterial function, which is the best for image registration of retina. Registration of images is very difficult; it is important to get some informations such as an uniqueness or a shape of function.
|
|
|
Multimodal retinal image registration
Štohanzlová, Petra ; CSc, Tomáš Suk, (referee) ; Harabiš, Vratislav (advisor)
This work deals with possibilities of registration of retinal images from different mo-dalities, concretely optical coherence tomography (OCT), scanning laser ophthalmoscopy (SLO) and fundus camera. In first stage is the interest focused on registration of SLO and fundus images, which will serve to determine area of interest for consecutive registration of OCT data. The final stage is finding correct location of OCT B-scans in fundus image. On the basis of the studied methods of registration was chosen method making use of computation of correlation coefficient for both cases. For finding optimal parameters of registration is used searching through whole space of parameters. In partial stages of the work was created algorithm for alignment of B-scans followed by detection of blood vessels and also simple algorithm for detection of blood vessels from fundus image. For more transparent registration the graphical user interface was created, which allows loading input images and displaying the result in several possible forms.
|
|
|
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.
|
|
|
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.
|
|
|
Analysis of vessel pulsation in retinal video sequences
Valentová, Vanessa ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Glaucoma is the third most common cause of blindness in the world. There are several types of glaucomma, which makes early diagnosis of this illness harder. One posibble way for early diagnosis could be analysis of a retinal vessel pulsation. Data in this work were captured by experimental device called video ophtalmoscope. Several methods for optic disc segmentation were designed. From segmented parts, pulsation curve was recorded. Analysis of the pulsation curve was provided in two ways: Analysis of the whole pulsation curve and Averaged pulse analysis. Both methods were tested with diferent reference signals.
|
|
|
Analysis of autofluorescence retinal images
Mosyurchak, Andriy ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Autofluorescence retinal images are obtained with a confocal laser scanning ophthalmoscope, and used for the diagnostic of glaucoma. Glaucoma causes a gradual death of nerve cells and can cause blindness. Retina autofluorescence is caused by pigment lipofuscin, which causes cell damage. The aim of this work was to study methods suitable for segmentation of autofluorescence zones and method for tracking objects in an image. In this project was implemented algorithm of autofluorescence zone detection using method of region growing, designed and realized method for tracking autofluorescence regions.
|
|
|
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.
|
|
|
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.
|
guest ::
