Computer‐aided detection systems aim at the automatic detection of diseases using
different medical imaging modalities. In this paper, a novel approach to detecting …

Since the discovery of X-rays and their applications, medical imaging has been a great help
for radiologists in the diagnosis of diseases. In recent years, there has been a great effort in …

This article presents a novel approach for the automatic detection of lesions and selection of
features on chest radiographs. We have illustrated the importance of accurate segmentation …

A novel framework for automatic detection of pneumothorax abnormality in chest
radiographs is presented. The suggested method is based on a texture analysis approach …

This paper presents a method that employs texture-based feature extraction and Support
Vector Machines (SVM) to classify chest abnormal radiograph patterns namely pleural …

A computer‐aided detection (CAD) system is presented for the localization of interstitial
lesions in chest radiographs. The system analyzes the complete lung fields using a two …

As the most common examination tool in medical practice, chest radiography has important
clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease …

The accurate quantification of disease patterns in medical images allows radiologists to
track the progress of a disease. Various computer vision techniques are able to …

In this paper we propose a scheme for automated detection of lung nodules in chest
radiographs. The proposed scheme first segments lungs in a chest image using an active …

Purpose: The aim of this study was to develop an automated method for detection of local
texture‐based and density‐based abnormalities in chest radiographs. Methods: The method …