  Relative location prediction in computed tomography (CT) scan images is a
challenging problem. In this paper, a regression model based on one-dimensional
convolutional neural networks is proposed to determine the relative location of
a CT scan image both robustly and precisely. A public dataset is employed to
validate the performance of the study's proposed method using a 5-fold cross
validation. Experimental results demonstrate an excellent performance of the
proposed model when compared with the state-of-the-art techniques, achieving a
median absolute error of 1.04 cm and mean absolute error of 1.69 cm.
