title: Automatic detection of lesions in lung regions that are segmented using spatial relations.
abstract: 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, which is based on spatial relationships between the lung structures, as a preprocessing step in a Computer Aided Diagnosis (CAD) scheme. Then, three suitable combinations of features have been identified using the forward stepwise selection method from the original images and their transformed ones. Experimental results show that our segmentation approach and the suppression of skeletal structures improve the detection accuracy. The selected features can describe efficiently different kinds of chest lesions.
authors.affiliation: LARODEC, Higher Institute of Management, University of Tunis, Tunisia. donia_ben_hassen@yahoo.fr
authors.forename: Donia Ben
authors.initials: DB
authors.lastname: Hassen
authors.forename: Hassen
authors.initials: H
authors.lastname: Taleb
mesh_terms: D000465:Algorithms; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity