Foreign Artifacts Detection on Pediatric Chest X-Ray

Abstract

Chest radiography is one of the recommended imaging tests by the World Health Organization for childhood pneumonia diagnosis. In computer-aided diagnostic systems where radiography is the main input, its quality is crucial. The presence of foreign artifacts can, therefore, compromise the performance of these systems. In the radiography exam, foreign artifacts are very common, especially in children, due to the ingestion of objects and the need for immobilization of these patients by third parties. Identification tags, shirt buttons, catheters, tubes and in conventional scanned radiographs, fingerprints, tags, noise and inadequate brightness are some of the artifacts present. In this study, we present an efficient and very simple method for detecting and removing artifacts based on common digital image processing operations such as channel subtraction, edge detection, and morphological operations. We describe the proposed method and evaluate its performance in a database of 200 images. We show that it is robust to identify different types of artifacts regardless of their positions on the radiography. A visual inspection was used to measure the errors and the experimental results showed an accuracy of 0.98 and a processing time of about 375ms per image. As a result of this, the method demonstrates to be a very promising pre-processing tool.