Tyshchenko, Bohdan - Search Results - Digital Repository

guest :: login Digital Repository
		Search		Submit		Help		About

Home > Search Results: Tyshchenko, Bohdan

Search:

Search Tips :: Advanced Search

Search collections:

Sort by:	Display results:	Output format:

	Detection of pathological vertebrae in spinal CTs utilised by machine learning methods Tyshchenko, Bohdan ; Ronzhina, Marina (referee) ; Chmelík, Jiří (advisor) 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. Detailed record
	Detection Of Pathological Vertebrae In Spinal Ct Utilised By Machine Learning Methods Tyshchenko, Bohdan This paper presents a computer aided detection system to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network (NN), which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features. Detailed record
	Detection of pathological vertebrae in spinal CTs utilised by machine learning methods Tyshchenko, Bohdan ; Ronzhina, Marina (referee) ; Chmelík, Jiří (advisor) 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. Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.

Digital Repository :: :: :: ::
Powered by v1.1.2
Maintained by

This site is also available in the following languages:
Česky English