This master's thesis focuses on detection of pathological vertebrae in spinal CT utilized by machine learning. Theoretical part describes anatomy of the spine and occurrence of pathologies in CT image data, contains an overview of existing methods intended for automated detection of pathological vertebrae. Practical part devotes to design a computer aided detection systems to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network, which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features. For completing this task were used real data. Conclusion contains evaluation of obtained results.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:401021 |
| Date | January 2019 |
| Creators | Tyshchenko, Bohdan |
| Contributors | Ronzhina, Marina, Chmelík, 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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