Fully Automatic Removal of Chest Tube Figures from Postero-Anterior Chest Radiographs

C. Ahmet Mercan and M. Serdar Celebi (Turkey)

Keywords

Convolutional Neural Network (CNN), Computer AidedDiagnosis (CAD), chest tube, artificial object, figure removing, chest radiography

Abstract

The presence of artificial objects in radiographic images is common. For example, 33% of chest radiographs contain catheters. Anomaly detection algorithms used to moni.tor disease progression should not be confused by artificial objects such as catheters, chest tubes, pacemakers or even cloths that might be present in chest radiographs. Hence, the detection and the removal of artificial objects via a preprocessing module are very useful for Computer Aided Diagnosis (CAD) research. In this paper, we propose a Convolutional Neural Network (CNN) architecture that works as a trainable filter that removes simulated chest tube figures from chest radiographs.

Important Links:

• DOI: 10.2316/P.2010.679-041
• From Proceeding (679) Computer Graphics and Imaging - 2010

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