• DocumentCode
    1253292
  • Title

    Automatic background recognition and removal (ABRR) in computed radiography images

  • Author

    Zhang, Jianguo ; Huang, H.K.

  • Author_Institution
    Dept. of Radiol., California Univ., San Francisco, CA, USA
  • Volume
    16
  • Issue
    6
  • fYear
    1997
  • Firstpage
    762
  • Lastpage
    771
  • 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, the authors achieved 99% correct recognition of CR image background, and 91% full background removal without removing any valid image information.
  • Keywords
    PACS; adaptive signal processing; diagnostic radiography; edge detection; image recognition; medical image processing; statistical analysis; X-ray collimation; adaptive parameter adjustment; angle recognition; automatic background recognition; automatic background removal; background pixels; computed radiography images; consistent reliable estimation rules; determine edges; filtering; hierarchical sample images; medical diagnostic imaging; projection radiographic examinations; specific sampling; statistical curve; Adaptive signal processing; Chromium; Collimators; Image recognition; Image sampling; Picture archiving and communication systems; Pixel; Radiography; Signal sampling; X-ray imaging; Humans; Image Processing, Computer-Assisted; Radiographic Image Enhancement; Radiology Information Systems;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.650873
  • Filename
    650873