  Much 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 (HFS) patient
position. The proposed method is based on the prediction of rotation angle with
CNN, and it achieved nearly perfect results with an accuracy of 99.55 %. We
provide implementations with easy to use an example for both Matlab and Python
(PyTorch), which can be used, for example, for automatic rotation correction of
VerSe2020 challenge data.
