JAKUBICEK, Roman, Jiri CHMELIK, Jiri JAN, Petr OUŘEDNÍČEK, Lukas LAMBERT and Giampaolo GAVELLI. Fully Automatic CAD System for Spine Localisation and Vertebra Segmentation in CT Data. In Lenka Lhotska; Lucie Sukupova; Igor Lacković; Geoffrey S. Ibbott. WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 1. NEW YORK: SPRINGER, 2019, p. 223-226. ISBN 978-981-10-9034-9. Available from: https://dx.doi.org/10.1007/978-981-10-9035-6_40.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Fully Automatic CAD System for Spine Localisation and Vertebra Segmentation in CT Data
Authors JAKUBICEK, Roman (203 Czech Republic, guarantor), Jiri CHMELIK (203 Czech Republic), Jiri JAN (203 Czech Republic), Petr OUŘEDNÍČEK (203 Czech Republic, belonging to the institution), Lukas LAMBERT (203 Czech Republic) and Giampaolo GAVELLI (380 Italy).
Edition NEW YORK, WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 1, p. 223-226, 4 pp. 2019.
Publisher SPRINGER
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 30224 Radiology, nuclear medicine and medical imaging
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL
RIV identification code RIV/00216224:14110/19:00113593
Organization unit Faculty of Medicine
ISBN 978-981-10-9034-9
ISSN 1680-0737
Doi http://dx.doi.org/10.1007/978-981-10-9035-6_40
UT WoS 000450908300040
Keywords in English Spine detection; Vertebra identification and segmentation; CADx; CT data; Oncological patient
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 7/4/2020 14:10.
Abstract
In this paper, we describe a fully automatic CAD system for spine detection in CT data followed by vertebra identification and segmentation. There are several basic problems: spine detection including the determination of spinal axis in spinal CT data, a localisation of individual vertebrae and identification of their types (order in spine) in case of incomplete scans of spine and also the final vertebra segmentation. By a subjective strict expert validation, the algorithm provides 82.6% of fully correct vertebra segmentations. Based on that, it seems to be routinely usable and fully applicable in preparation for the following automatic spine bone lesion analysis.
PrintDisplayed: 23/6/2024 10:05