# A deep learning-based method for relative location prediction in CT scan images

arXiv: https://arxiv.org/abs/1711.07624 · HTML: https://mlsanity.com/paper/1711.07624/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2017.

## Built on by (most cited first, 1 of 1)

- [Fast CT anatomic localization algorithm](https://mlsanity.com/paper/2312.02941/) (2023)

## Abstract (arXiv)

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.