|
|
Segmentation of choroid blood vessels in 3D images from optical coherence tomography
Maňkoš, Richard ; Kolář, Radim (referee) ; Štohanzlová, Petra (advisor)
This project deals with segmentation of choroid blood vessels in 3D images from optical coherence tomography. The first part is dedicated to theoretical description of the human eye. The second part describes basic information about the optical coherence tomography. In the third part two techniques, which are used on the blood vessels segmentation are described. The last part is practical and deals with an image processing in software OCTSEG and with own created algorithm for blood vessel segmentation.
|
|
|
Artifact elimination in optical coherence tomography images
Handová, Denisa ; Kolář, Radim (referee) ; Štohanzlová, Petra (advisor)
This work deals with familiarization with optical coherence tomography. It is divided into the several parts. The introductory part of the work describes the principle of this method, the mathematical explanation and characterization of two options for data acquisition - Time-domain OCT and Fourier-domain OCT. Below, the possibilities of using this technique in medicine, in ophthalmology, cardiology and neurology are described. The third part deals with the description of the artifacts and ways of their elimination. The work also includes solution for the reduction of these artifacts in MATLAB and this solution is used in the user application to remove artifact elimination in optical coherence tomography images. At the end, there are the examples of the measured and processed data
|
|
|
Visualization of 3D data in biomedical applications
Karzel, Michal ; Harabiš, Vratislav (referee) ; Štohanzlová, Petra (advisor)
This thesis describes the basic principle of optical coherence tomography and prepro- cessing of the measured raw data. Preprocessing is focused mainly on noise filtration, removing artifacts, normalization, conversion and compression of raw data. In this way preprocessed data is saved in a *. PFRG file as ”preprocessed fringe data”. Those pre- processed data will be visualised by simply software, which support three methods of visualisation. Volume data represented by voxels. Reconstruction of volume by marching cube algorithm. Cuts through volume along X, Y and Z axis.
|
|
|
Statistical analysis of images from optical coherence tomography with retinal applications
Kelča, Jan ; Slávik, Vladimír (referee) ; Kolář, Radim (advisor)
This work briefly describes the anatomy of the eye and retinal structure, including its pathological changes. The work is focused on the characteristics and the principle of optical coherence tomography and its application in ophthalmology in conjunction with statistical analysis of retinal images. The practical part explains problems of statistical analysis retinal images using histograms representing the distribution of gray shades and approximation of functions, which are stretched exponential function and Nakagami function. Suitable optimalization are obtained parameters, from which are formed parametric maps illustrating the distribution of gray levels in different areas of interest.
|
|
|
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.
|
|
|
Extracting of the optic disc in optical coherence tomography images
Šeda, Jan ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
The main target of this work is a design of the program for border localization of the optic disc in OCT data. Part of this program is also localization of the „optic cup“ and calculation of several values that characterize optic disc. The work is also dealing with a description of the optical coherence tomography principle which is used in ophthalmology. One chapter describes some published methods of optic cup localization. Success of the program and its comparison with OCT Zeiss Stratus 3000 is evaluated at the end of the work.
|
|
|
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.
|
|
|
Intra-retinal layer segmentation in optical coherence tomography images
Zlotý, Petr ; Kolář, Radim (referee) ; Gazárek, Jiří (advisor)
This work describes optical coherence tomography, it's principle and methods for automatic segmentation intra-retinal layers in OCT images . There is proposed algorithm for boundary detection of two intra retinal layers, RFNL and RPE layer based on thresholding and second algorithm for detection of seven layers, which is based on graph search algorithm. In summary is compared accuracy against manualy segmented layers and there is also proposed solution for problematic parts.
|
|
|
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.
|
guest ::
