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Image segmentation of spinal disc in medical imaging
Meloun, Jan ; Nemček, Jakub (referee) ; Mézl, Martin (advisor)
The thesis is focused on the segmentation of the intervertebral disc in the image data.The introduction deals with the issue of the spine, the herniation of the intervertebraldisc. It also deals with imaging modalities, especially computed tomography and mag-netic resonance imaging. The practical part describes the image data segmentation andthe implementation of three of the published segmentation methods.
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Vegetation Detection in Images
Černá, Tereza ; Herout, Adam (referee) ; Přibyl, Bronislav (advisor)
This project focuses on detection of vegetation in digital image and describes approaches to detect vegetation. Created aplication uses grass detection method in video in real time. There is a new mean of evaluation of the method proposed in this project, using commonly used pixel by pixel detection and also a new detection approach, segment detection. Functionality of the application is checked by set of test images. The thesis is concluded by comparing results of those two approaches. Success of correctly detected vegetation ranges up to 86.32 %.
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Image segmentation based on relief
Gros, Jan ; Špiřík, Jan (referee) ; Křupka, Aleš (advisor)
The aim of this labor is to introduce the technique of image segmentation by flooding relief of landscape (watershed method). There are described some methods of image segmentation and explained the basic operations of the images, from which the morphological operations are used for watershed segmentation. Part of this labor is a short passage that deals with the use of some image filters for image preprocessing. The result of previous knowledge is presentation of segmentation algorithm designed by Lee Vincent and Pierre Soille. The next section describes the algorithm implementation in Java, contents and function of each class module and implementation using RapidMiner. The last section presents the results of the segmentation with created module using the test images without and with the use of some selected filters to reduce oversegmentation and improve the resulting segmentation.
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Image segmentation of spinal disc in medical imaging
Meloun, Jan ; Nemček, Jakub (referee) ; Mézl, Martin (advisor)
The thesis is focused on the segmentation of the intervertebral disc in the image data.The introduction deals with the issue of the spine, the herniation of the intervertebraldisc. It also deals with imaging modalities, especially computed tomography and mag-netic resonance imaging. The practical part describes the image data segmentation andthe implementation of three of the published segmentation methods.
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Image segmentation based on relief
Gros, Jan ; Špiřík, Jan (referee) ; Křupka, Aleš (advisor)
The aim of this labor is to introduce the technique of image segmentation by flooding relief of landscape (watershed method). There are described some methods of image segmentation and explained the basic operations of the images, from which the morphological operations are used for watershed segmentation. Part of this labor is a short passage that deals with the use of some image filters for image preprocessing. The result of previous knowledge is presentation of segmentation algorithm designed by Lee Vincent and Pierre Soille. The next section describes the algorithm implementation in Java, contents and function of each class module and implementation using RapidMiner. The last section presents the results of the segmentation with created module using the test images without and with the use of some selected filters to reduce oversegmentation and improve the resulting segmentation.
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Vegetation Detection in Images
Černá, Tereza ; Herout, Adam (referee) ; Přibyl, Bronislav (advisor)
This project focuses on detection of vegetation in digital image and describes approaches to detect vegetation. Created aplication uses grass detection method in video in real time. There is a new mean of evaluation of the method proposed in this project, using commonly used pixel by pixel detection and also a new detection approach, segment detection. Functionality of the application is checked by set of test images. The thesis is concluded by comparing results of those two approaches. Success of correctly detected vegetation ranges up to 86.32 %.
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