Detail publikace

A Tool for Automatic Estimation of Patient Position in Spinal CT Data

JAKUBÍČEK, R. VIČAR, T. CHMELÍK, J.

Originální název

A Tool for Automatic Estimation of Patient Position in Spinal CT Data

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Most of the recently available research and challenge data lack the meta-data containing any information about the patient position. This paper presents a tool for automatic rotation of CT data into a standardized (Head First Supine) patient position. The proposed method is based on the prediction of rotation angle with convolutional neural network, and it achieved nearly perfect results with an accuracy of 99.55 %. We provide implementations with easy to use example for both, Matlab and Python (PyTorch), which can be used, for example, for automatic rotation correction of VerSe2020 challenge data.

Klíčová slova

Patient position estimation; Convolutional neural network; Computed tomography

Autoři

JAKUBÍČEK, R.; VIČAR, T.; CHMELÍK, J.

Vydáno

30. 11. 2020

Nakladatel

Springer Nature Switzerland AG 2021

Místo

Switzerland

ISBN

978-3-030-64610-3

Kniha

EMBEC 2020, IFMBE Proceedings 80

ISSN

1680-0737

Periodikum

IFMBE PROCEEDINGS

Ročník

80

Stát

Švédské království

Strany od

51

Strany do

56

Strany počet

6

URL

https://link.springer.com/chapter/10.1007/978-3-030-64610-3_7

BibTex

@inproceedings{BUT166032,
  author="Roman {Jakubíček} and Tomáš {Vičar} and Jiří {Chmelík}",
  title="A Tool for Automatic Estimation of Patient Position in Spinal CT Data",
  booktitle="EMBEC 2020, IFMBE Proceedings 80",
  year="2020",
  journal="IFMBE PROCEEDINGS",
  volume="80",
  pages="51--56",
  publisher="Springer Nature Switzerland AG 2021",
  address="Switzerland",
  doi="10.1007/978-3-030-64610-3\{_}7",
  isbn="978-3-030-64610-3",
  issn="1680-0737",
  url="https://link.springer.com/chapter/10.1007/978-3-030-64610-3_7"
}