Tissue Characterisation In Spectral Ct Data
| but.event.date | 25.04.2019 | cs |
| but.event.title | Student EEICT 2019 | cs |
| dc.contributor.author | Poláková, Veronika | |
| dc.date.accessioned | 2020-04-16T07:19:26Z | |
| dc.date.available | 2020-04-16T07:19:26Z | |
| dc.date.issued | 2019 | cs |
| dc.description.abstract | This article deals with tissue characterisation in virtual monoenergetic images (VMI). It presents that with growing energy of VMI the median of CT number increases or decreases with different steepness depending on a type of tissue. As a consequence, some VMI enable better soft tissue distinction and therefore their better classification. To determine which VMI are best suited, Cohen d was used. After that, Random Forest classification algorithm was applied to these images. If median of pixels is considered in addition to pixels themselves, the tissues can be clasiffied correctly. | en |
| dc.format | text | cs |
| dc.format.extent | 46-49 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Proceedings of the 25st Conference STUDENT EEICT 2019. s. 46-49. ISBN 978-80-214-5735-5 | cs |
| dc.identifier.isbn | 978-80-214-5735-5 | |
| dc.identifier.uri | http://hdl.handle.net/11012/186614 | |
| dc.language.iso | cs | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.relation.ispartof | Proceedings of the 25st Conference STUDENT EEICT 2019 | en |
| dc.relation.uri | http://www.feec.vutbr.cz/EEICT/ | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.rights.access | openAccess | en |
| dc.subject | spectral CT | en |
| dc.subject | image segmentation | en |
| dc.subject | descriptive statistics | en |
| dc.subject | supervised machine learning | en |
| dc.title | Tissue Characterisation In Spectral Ct Data | en |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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