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
Link To Document :
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