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JAKUBÍČEK, R.; VIČAR, T.; CHMELÍK, J.
Original Title
A Tool for Automatic Estimation of Patient Position in Spinal CT Data
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
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.
English abstract
Keywords
Patient position estimation; Convolutional neural network; Computed tomography
Key words in English
Authors
RIV year
2021
Released
30.11.2020
Publisher
Springer Nature Switzerland AG 2021
Location
Switzerland
ISBN
978-3-030-64610-3
Book
EMBEC 2020, IFMBE Proceedings 80
1680-0737
Periodical
IFMBE Proceedings
Volume
80
State
French Republic
Pages from
51
Pages to
56
Pages count
6
URL
https://link.springer.com/chapter/10.1007/978-3-030-64610-3_7
Full text in the Digital Library
http://hdl.handle.net/
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" }
Documents
506237_1_En_7_Chapter_Author-3