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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137804" target="_blank" >RIV/00216305:26220/20:PU137804 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-64610-3_7" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-64610-3_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-64610-3_7" target="_blank" >10.1007/978-3-030-64610-3_7</a>

Result language
angličtina
Original language name
A Tool for Automatic Estimation of Patient Position in Spinal CT Data
Original language description
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.
Czech name
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Czech description
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Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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