A New Stochastic Model-Based Image Segmentation Technique For X-Ray CT Image

Tianhu Lei; Wilfred Sewchand

doi:10.1117/12.968960

25 October 1988 A New Stochastic Model-Based Image Segmentation Technique For X-Ray CT Image

Tianhu Lei, Wilfred Sewchand

Proceedings Volume 1001, Visual Communications and Image Processing '88: Third in a Series; (1988) https://doi.org/10.1117/12.968960
Event: Visual Communications and Image Processing III, 1988, Cambridge, MA, United States

Abstract

This manuscript demonstrates that X-ray CT image can be modeled by a finite normal mixture. The number of image classes in the observed image is detected by the information criteria (AIC or MDL). Parameters of the model are estimated by a modified K-mean algorithm and Bayesian decision criterion is the basis for this image segmentation approach. The use of simulated and real image data demonstrate the very promising results of this proposed technique.

Citation Download Citation

Tianhu Lei and Wilfred Sewchand "A New Stochastic Model-Based Image Segmentation Technique For X-Ray CT Image", Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); https://doi.org/10.1117/12.968960

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