Druh výsledku
článek ve sborníku
Popis
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.
