A. S. Markov, E. Yu. Kotlyarov, N. P. Anosova, V. A. Popov, I. Karandashev, D. E. Apushkinskaya, “Using neural networks to detect anomalies in X-ray images obtained with full-body scanners”, Avtomat. i Telemekh., 2022, Issue 10,Pages <nobr>23

This article is cited in 2 papers

Topical issue

Using neural networks to detect anomalies in X-ray images obtained with full-body scanners

A. S. Markov^a, E. Yu. Kotlyarov^a, N. P. Anosova^a, V. A. Popov^a, I. Karandashev^ba, D. E. Apushkinskaya^a

^a RUDN University, Moscow, 117198 Russia
^b Institute for Systems Analysis, Russian Academy of Sciences, Moscow, 117218 Russia

Abstract: In this paper, we solve the problem of detecting anomalies in X-ray images obtained by full-body scanners (FBSs). The paper describes the sequence and description of image preprocessing methods used to convert the original images obtained with an FBS to images with visually distinguishable anomalies. Examples of processed images are given. The first (preliminary) results of using a neural network for anomaly detection are shown.

Keywords: full-body scanner, X-ray image, anomaly detection, image histogram equalization, neural network, U-2-Net.

Presented by the member of Editorial Board: A. A. Lazarev

Received: 01.02.2022
Revised: 31.05.2022
Accepted: 29.06.2022

DOI: 10.31857/S0005231022100038