title: Nodule detection in digital chest radiography: effect of nodule location.
abstract: Most detection studies in chest radiography treat the entire chest image as a single background or divided into the two regions parenchyma and mediastinum. However, the different parts of the lung show great variations in attenuation and structure, leading to different amounts of quantum noise and scattered radiation as well as different complexity. Detailed data on the difference in detectability in the different regions are of importance. The purpose of this study was to quantify the difference in detectability between different regions of a chest image. The chest X ray was divided into six different regions, where each region was considered to be uniform in terms of detectability. Thirty clinical chest images were collected and divided into the different regions. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrast were added to the images. An equal number of images lacking pathology were included and a receiver operating characteristic (ROC) study was conducted with five observers. Results show that the image contrast needed to obtain a constant value of A(z) (area under an ROC curve) differs by more than a factor of four between different regions.
authors.affiliation: Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, SE-413 45 Göteborg, Sweden. markus.hakansson@vgregion.se
authors.forename: Markus
authors.initials: M
authors.lastname: Håkansson
authors.forename: Magnus
authors.initials: M
authors.lastname: Båth
authors.forename: Sara
authors.initials: S
authors.lastname: Börjesson
authors.forename: Susanne
authors.initials: S
authors.lastname: Kheddache
authors.forename: Agneta
authors.initials: A
authors.lastname: Flinck
authors.forename: Gustaf
authors.initials: G
authors.lastname: Ullman
authors.forename: Lars Gunnar
authors.initials: LG
authors.lastname: Månsson
mesh_terms: D016477:Artifacts; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging* / Q000473:pathology; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D008953:Models, Anatomic; D009010:Monte Carlo Method; D015588:Observer Variation; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011859:Radiography / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D012542:Scattering, Radiation; D012984:Software; D014965:X-Rays