title: Lung segmentation in digital radiographs.
abstract: Computer-assisted interpretation of computer radiography (CR) chest images including lung nodules detection, quantitative texture analysis, etc requires a lung delineation algorithm that restricts the area to be analyzed. This report presents a new lung-segmentation technique. It is performed in three phases. First, a histogram analysis finds a threshold value that eliminates the densest anatomic regions. Then, a gradient analysis separates the lungs from parts of thorax attached to the lungs that have not been removed in the previous phase. A smoothing routine yields the final image. By imposing a testing condition that results from the histogram analysis, underexposed images are not being considered. If being segmented, they exhibit a significant lung penetration. The test increases the accuracy of the procedure and makes it safer for an unsupervised application. The segmentation procedure has been implemented together with preprocessing functions in our clinical picture archiving and communication system.
authors.affiliation: University Hospital of Geneva, Medical Imaging Unit, Switzerland.
authors.forename: E
authors.initials: E
authors.lastname: Pietka
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement; D011873:Radiology Information Systems