Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility.
J Digit Imaging
; 12(1): 34-42, 1999 Feb.
Article
em En
| MEDLINE
| ID: mdl-10036666
ABSTRACT
The purpose of this study was to develop and test a computerized method for the fully automated analysis of abnormal asymmetry in digital posteroanterior (PA) chest radiographs. An automated lung segmentation method was used to identify the aerated lung regions in 600 chest radiographs. Minimal a priori lung morphology information was required for this gray-level thresholding-based segmentation. Consequently, segmentation was applicable to grossly abnormal cases. The relative areas of segmented right and left lung regions in each image were compared with the corresponding area distributions of normal images to determine the presence of abnormal asymmetry. Computerized diagnoses were compared with image ratings assigned by a radiologist. The ability of the automated method to distinguish normal from asymmetrically abnormal cases was evaluated by using receiver operating characteristic (ROC) analysis, which yielded an area under the ROC curve of 0.84. This automated method demonstrated promising performance in its ability to detect abnormal asymmetry in PA chest images. We believe this method could play a role in a picture archiving and communications (PACS) environment to immediately identify abnormal cases and to function as one component of a multifaceted computer-aided diagnostic scheme.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Intensificação de Imagem Radiográfica
/
Pneumopatias
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Digit Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
/
INFORMATICA MEDICA
/
RADIOLOGIA
Ano de publicação:
1999
Tipo de documento:
Article
País de afiliação:
Estados Unidos