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JAKUBÍČEK, R. CHMELÍK, J. OUŘEDNÍČEK, P. JAN, J.
Originální název
Deep-learning-based fully automatic spine centerline detection in CT data
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
In this contribution, we present a fully automatic approach, that is based on two convolution neural networks (CNN) together with a spine tracing algorithm utilizing a population optimization algorithm. Based on the evaluation of 130 CT scans including heavily distorted and complicated cases, it turned out that this new combination enables fast and robust detection with almost 90% of correctly determined spinal centerlines with computing time of fewer than 20 seconds.
Klíčová slova
CT; spine centerline; machine learning
Autoři
JAKUBÍČEK, R.; CHMELÍK, J.; OUŘEDNÍČEK, P.; JAN, J.
Vydáno
7. 10. 2019
Nakladatel
IEEE
Místo
Berlin, Germany
ISBN
978-1-5386-1312-2
Kniha
2019 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Číslo edice
19
ISSN
1557-170X
Periodikum
Proceedings IEEE EMBC
Ročník
Stát
Spojené státy americké
Strany od
2407
Strany do
2410
Strany počet
4
URL
https://ieeexplore.ieee.org/document/8856528
BibTex
@inproceedings{BUT157840, author="Roman {Jakubíček} and Jiří {Chmelík} and Petr {Ouředníček} and Jiří {Jan}", title="Deep-learning-based fully automatic spine centerline detection in CT data", booktitle="2019 41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)", year="2019", journal="Proceedings IEEE EMBC", volume="19", number="19", pages="2407--2410", publisher="IEEE", address="Berlin, Germany", doi="10.1109/EMBC.2019.8856528", isbn="978-1-5386-1312-2", issn="1557-170X", url="https://ieeexplore.ieee.org/document/8856528" }