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Visualization of Marked Cells of a Model Organism
Kubíček, Radek ; Kršek, Přemysl (referee) ; Herout, Adam (advisor)
This master thesis is focused on volumetric data rendering and on highlighting and visualization of the selected cells of the model organisms. These data are captured by a confocal deconvolution microscope. Input data form one large volumetric block containing separate slices. This data block is rendered by an applicable method and then are identified and visualized the cells marked by the GFP (Green Fluorescent Protein) process or by chlorophyle fluorescency. The principal aim of this work is to find out the preferably optimal effective method enabling this highlighting, most preferably working without a manual check. Due to the data structure, this ambition seems hardly realizable, so it suffices to find out a manual working method. The last step is to embed the results of this work into FluorCam application, the confocal deconvolution microscope data visualizer.
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CPU Rendering of Large Volumetric Data
Svoboda, Jan ; Vlnas, Michal (referee) ; Španěl, Michal (advisor)
This thesis deals with design and implementation of a system that allows displaying large volumetric data in real time on the CPU of a conventional computer. The thesis aims to solve two biggest problems. Firstly, it aims to solve the problem with rendering itself, where this amount of data often cannot be placed into the main memory of a target computer. Secondly, it aims to solve the problem of storing of this data, where, in the case of large datasets, storing them in the storage of a target computer may not be desirable. The proposed solution contains two applications -- the server one and the client one. The server part is used as a remote storage of volumetric data that is provided to the client application in small blocks and in different qualities. The client application renders this data by the ray casting method and, according to the created strategies, performs loading and storing of required blocks in the local memory. In order to achieve high performance, the client application was implemented with an emphasis on parallelization of the main processes. The resulting system allows a user to display large datasets stored on a server's storage and to manage the datasets using a simple graphical user interface.
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Visualization of Large Volumetric Data on CPU
Dlabaja, Drahomír ; Milet, Tomáš (referee) ; Španěl, Michal (advisor)
This thesis deals with the problem of displaying volumetric data that exceeds the operating memory capacity of the machine. The work describes the design of a visualization pipeline, which consists of a data structure for large volumetric data and an algorithm that visualizes such data. The proposed hierarchical data structure accelerates sampling and allows the reduction of the total amount of data that needs to be loaded into physical memory during visualization. Visualization of processed data is achieved by the ray casting method with existing optimization techniques, such as empty space skipping and early ray termination. The data structure allows up to 12x faster sampling compared to the sampling of raw large volumetric data serialized by rows. Up to 150x faster visualization of large volumetric data in near-lossless mode has been achieved compared to the fully lossless mode by utilizing the data hierarchy. The display scheme is implemented in the form of a library in C++20 language. The implementation uses acceleration by vectorization and allows easy parallelization by the user. The library provides tools for processing and visualization of large volumetric data on the CPU.
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Software for visualization and processing of volumetric data
Viktorínová, Michaela ; Jakubíček, Roman (referee) ; Harabiš, Vratislav (advisor)
The work summarizes the possibilities of volume data displaying. It deals with the scalar type of volume algorithms, which are then divided into techniques of indirect and direct rendering of volume data. From indirect techniques the Marching Cubes method is mentioned. Direct techniques are further divided into trivial and advanced algorithms. The practical part describes the design, implementation and evaluation of the functionality of implemented program that uses trivial methods. The overall evaluation consists of partial evaluations of the computational complexity, the memory load and the quality of final rendering while using different methods and types of input volume data.
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Organ segmentation
Kolomazník, Jan
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Segmentation and density estimation in femur
Horáček, Jan ; Maršálek, Lukáš (advisor)
Title: Segmentation and Density Estimation in Femur Author: Jan Horáček Department: Department of Software and Computer Science Education Supervisor: Mgr. Lukáš Maršálek Supervisor's e-mail address: lukas.marsalek@mff.cuni.cz Abstract: There are two basic ways of surgical treatment of femoral neck frac- ture - total endoprosthesis or a special metal screw in the bone. In case of a dense enough bone the screws are preferred. But for a too sparse bone, the screw may cut through the femoral head, which results in further surgical operations. We present a novel method for femoral head density measurement, which serves as another hint for the doctor's decision, whether to apply a screw or total endo- prosthesis. Our approach is based on semi-automatical femoral head segmenta- tion from CT dataset based on finding optimal path through polar coordinates on axial slices. The cost function is based on a combination of corticallis proper- ties, mostly the directional behavior of 3D gradients and their size in 2D slices, where they form typical "channels". The final volume is computed using filling and morphological algorithms and its properties are further measured. The final implementation was experimentally validated on RTG clinic of Bulovka hospital and allows radiologists to intuitively and accurately estimate...
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Displaying 3D Graphics in Web Browser
Sychra, Tomáš ; Pečiva, Jan (referee) ; Španěl, Michal (advisor)
This thesis discusses possibilities of accelerated 3D scene displaying in a Web browser. In more detail, it deals with WebGL standard and its use in real applications. An application for visualization of volumetric medical data based on JavaScript, WebGL and Three.js library was designed and implemented. Image data are loaded from Google Drive cloud storage. An important part of the application is 3D visualization of the volumetric data based on volume rendering technique called Ray-casting.
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Medical Image Segmentation
Lipták, Juraj ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with a graph cut approach for segmentation of the anatomical structures in volumetric medical images. The method used requires some voxels to be a priori identified as object or background seeds. The goal of this thesis is implementation of the graph cut method and construction of an interactive tool for segmentation. Selected metod's behaviour is examined on two datasets with manually-guided segmentation results. Testing is in one case focused on the influence of method parameters on segmentation results, while in the other deals with method tolerance towards various signal-to-noise and contrast-to-noise ratios on input. To assess the consistency of a given segmentation with the ground-truth the F-measure is used.
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Acceleration of 3D Image Processing Using GPU
Kozovský, Radoslav ; Klepárník, Petr (referee) ; Španěl, Michal (advisor)
p { margin-bottom: 0.21cm; direction: ltr; color: rgb(0, 0, 0); line-height: 150%; }p.western { font-family: "Times New Roman",serif; font-size: 11pt; }p.cjk { font-family: "Times New Roman",serif; font-size: 11pt; }p.ctl { font-family: "Times New Roman",serif; font-size: 12pt; } The aim of this work is to accelerate the calculation of selected 2D and 3D image filters using GPU using OpenCL. Specifically, it deals with the implementation and comparison of various variants of Sobel's edge detector and Gauss filter using global or local memory. Acceleration has been achieved on 3D filter variants. On 2D filter variants, the overhead for data transfer to and from the GPU was too high.
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