DocumentCode
1479647
Title
A methodology for modeling the distributions of medical images and their stochastic properties
Author
Zhang, Ya-Qin ; Loew, Murray H. ; Pickholtz, Raymond L.
Author_Institution
Dept. of Electr. & Comput. Eng., George Washington Univ., Washington, DC, USA
Volume
9
Issue
4
fYear
1990
fDate
12/1/1990 12:00:00 AM
Firstpage
376
Lastpage
383
Abstract
The probabilistic distribution properties of a set of medical images are studied. It is shown that the generalized Gaussian function provides a good approximation to the distribution of AP chest radiographs. Based on this result and a goodness-of-fit test, a generalized Gaussian autoregressive model (GGAR) is proposed. Its properties and limitations are also discussed. It is expected that the GGAR model will be useful in describing the stochastic characteristics of some classes of medical images and in image data compression and other applications
Keywords
diagnostic radiography; modelling; stochastic processes; AP chest radiographs; generalized Gaussian autoregressive model; generalized Gaussian function; goodness-of-fit test; image data compression; image stochastic properties; medical images distribution modeling; Biomedical imaging; Data compression; Entropy; Gaussian distribution; Histograms; Physics; Probability density function; Radiography; Stochastic processes; Testing;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/42.61753
Filename
61753
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