title: X-ray categorization and spatial localization of chest pathologies.
abstract: In this study we present an efficient image categorization system for medical image databases utilizing a local patch representation based on both content and location. The system discriminates between healthy and pathological cases and indicates the subregion in the image that is automatically found to be most relevant for the decision. We show an application to pathology-level categorization of chest x-ray data, the most popular examination in radiology. Experimental results are provided on chest radiographs taken from routine hospital examinations.
authors: BioMedical Engineering Tel-Aviv University, Israel.
authors: Uri
authors: U
authors: Avni
authors: Hayit
authors: H
authors: Greenspan
authors: Jacob
authors: J
authors: Goldberger
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D003936:Diagnosis, Computer-Assisted; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007802:Language; D015233:Models, Statistical; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D011871:Radiology / Q000379:methods; D012680:Sensitivity and Specificity; D013909:Thorax / Q000473:pathology*; D014965:X-Rays