Detail publikace

Deep-learning-based fully automatic spine centerline detection in CT data

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

19

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"
}