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Segmentation of Hippocampus in MRI Data
Kodym, O.
This project deals with application of graph-based methods in segmentation of low contrast image data, specifically hippocampus in MRI data. Using graph cuts for the segmentation allows the software to utilize high accuracy, robustness and an ability to interact with the user.
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Polygonal Mesh Segmentation
Švancár, Matúš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This bachelor thesis analyzes and approaches the issue of segmentation of polygonal models. It presents a design of an interactive method inspired by the method described in the Interactive Mesh Segmentation Based on Feature Preserving Harmonic Field. The method uses graph-cut and is implemented as a web application. The application supports .obj and .stl file formats, allows the user to load a model, draw sketches representing foreground and background on the surface of the model, and to start segmentation. Once completed, the user can download the resulting models or continue segmenting with one of them.
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Segmentation of hippocampus in MRI data
Kodym, Oldřich ; Chmelík, Jiří (referee) ; Walek, Petr (advisor)
The thesis deals with application of graph-based methods in segmentation of low contrast image data, specifically hippocampus segmentation from magnetic resonance data. Firstly, basics and terminology of graph theory is introduced. Next, minimum graph cut method is explained along with algorithms capable of finding this cut. After that comes the description of its implementation for 2D and 3D image data segmentation. Method was tested on sample data and then implemented as a 3D Slicer software module. Here the method was tested on the hipocampus data of healthy patients as well as patients suffering from Alzheimer’s disease. Most common problems occuring during the segmentation were forshadowed as well as possible ways to solve them.
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Interactive Foreground/Background Segmentation on Mobile Phone
Studený, Petr ; Szentandrási, István (referee) ; Herout, Adam (advisor)
This thesis deals with the problem of foreground extraction on mobile devices. The main goal of this project is to find or design segmentation methods for separating a user-selected object from an image (or video). The main requirement of these methods is the image processing time and segmentation quality. Some existing solutions of this problem are mentioned and their usability on mobile devices is discussed. A mobile application is created within the project, demonstrating the implemented real time foreground extraction algorithm.
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Medical image segmentation based on graph cut with shape prior
Kozlová, Dominika ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This thesis deals with a graph-based image segmentation and its improvement by using the information about the shape of the object for creating specific graph architecture (template). There are described basics of the graph theory, which is the basis of the graph segmentation methods. Designed segmentation algorithm was realized in 2D with graphical user interface in MATLAB. For segmentation of volume data, the method was extended into 3D. Implemented method was tested on simulated data and on real CT and MRI images of vertebra and brain. Obtained results were evaluated and compared with the original method without using the template.
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Polygonal Mesh Segmentation
Švancár, Matúš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This bachelor thesis analyzes and approaches the issue of segmentation of polygonal models. It presents a design of an interactive method inspired by the method described in the Interactive Mesh Segmentation Based on Feature Preserving Harmonic Field. The method uses graph-cut and is implemented as a web application. The application supports .obj and .stl file formats, allows the user to load a model, draw sketches representing foreground and background on the surface of the model, and to start segmentation. Once completed, the user can download the resulting models or continue segmenting with one of them.
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Medical Image Segmentation Based on Graph Cut with Shape Prior
Kozlová, Dominika
This paper deals with a graph-based image segmentation and its improvement by using the information about the shape of the object for creating specific graph architecture (template). Improved method allows the cut to prefer more complicated structures, especially when the image contains a lot of noise and the object is hardly indistinguishable from the background. Algorithm was tested on simulated data and real CT and MRI images of vertebra and brain in 2D. Method was also extended to 3D further purposes.
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Interactive Foreground/Background Segmentation on Mobile Phone
Studený, Petr ; Szentandrási, István (referee) ; Herout, Adam (advisor)
This thesis deals with the problem of foreground extraction on mobile devices. The main goal of this project is to find or design segmentation methods for separating a user-selected object from an image (or video). The main requirement of these methods is the image processing time and segmentation quality. Some existing solutions of this problem are mentioned and their usability on mobile devices is discussed. A mobile application is created within the project, demonstrating the implemented real time foreground extraction algorithm.
|
|
|
Segmentation of hippocampus in MRI data
Kodym, Oldřich ; Chmelík, Jiří (referee) ; Walek, Petr (advisor)
The thesis deals with application of graph-based methods in segmentation of low contrast image data, specifically hippocampus segmentation from magnetic resonance data. Firstly, basics and terminology of graph theory is introduced. Next, minimum graph cut method is explained along with algorithms capable of finding this cut. After that comes the description of its implementation for 2D and 3D image data segmentation. Method was tested on sample data and then implemented as a 3D Slicer software module. Here the method was tested on the hipocampus data of healthy patients as well as patients suffering from Alzheimer’s disease. Most common problems occuring during the segmentation were forshadowed as well as possible ways to solve them.
|
|
|
Medical image segmentation based on graph cut with shape prior
Kozlová, Dominika ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This thesis deals with a graph-based image segmentation and its improvement by using the information about the shape of the object for creating specific graph architecture (template). There are described basics of the graph theory, which is the basis of the graph segmentation methods. Designed segmentation algorithm was realized in 2D with graphical user interface in MATLAB. For segmentation of volume data, the method was extended into 3D. Implemented method was tested on simulated data and on real CT and MRI images of vertebra and brain. Obtained results were evaluated and compared with the original method without using the template.
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