title: Automatic background recognition and removal (ABRR) in computed radiography images.
abstract: A novel method to automatically recognize and remove background signals in computed radiography (CR) images caused by X-ray collimation during projection radiographic examinations is presented. There are three major steps in this method. In the first step, a statistical curve is derived based on many hierarchical CR sample images as a first approximation to loosely separate image and background pixels. Second, signal processing methods, including specific sampling, filtering, and angle recognition, are used to determine edges between image and background pixels. Third, adaptive parameter adjustments and consistent and reliable estimation rules are used to finalize the location of edges and remove the background. In addition, this step also evaluates the reliability of the complete background removal operation. With this novel method implemented in a clinical picture archiving and communication system (PACS) at the University of California at San Francisco, we achieved 99% correct recognition of CR image background, and 91% full background removal without removing any valid image information.
authors.affiliation: Department of Radiology, University of California, San Francisco 94143-0628, USA. jianguo-zhang@radmacl.ucsf.edu
authors.forename: J
authors.initials: J
authors.lastname: Zhang
authors.forename: H K
authors.initials: HK
authors.lastname: Huang
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011873:Radiology Information Systems