This thesis first describes theory of range of methods of textural and shape analysis. In several published articles some of the mentioned methods are used for automatic detection of lesion in spine in CT images. Some of these articles are shortly presented (in this thesis). Next part of the thesis includes description of various classifiers which are used for classification of feature vectors. Practical part of the thesis is a design and implementation of image data segmentation solution (metastatic lesions in vertebrae) with use of classification of feature vectors formed by texture and shape symptoms. The thesis also deals with the selection of significant features for segmentation. Segmentation algorithm is tested on medical data.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:221144 |
| Date | January 2014 |
| Creators | Novosadová, Michaela |
| Contributors | PhD, Miloš Malínský,, Jan, Jiří |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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