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

Roman Jakubicek; Jiri Chmelik; Petr Ourednicek; Jiri Jan

doi:10.1109/EMBC.2019.8856528

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

Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul:2019:2407-2410. doi: 10.1109/EMBC.2019.8856528.

Authors

Roman Jakubicek, Jiri Chmelik, Petr Ourednicek, Jiri Jan

PMID: 31946384
DOI: 10.1109/EMBC.2019.8856528

Abstract

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Deep Learning*
Humans
Neural Networks, Computer*
Spine* / diagnostic imaging
Tomography, X-Ray Computed