In Proc. IEEE Int. Conf. Image Processing, Vol. II, pp. 145-147, 1994

Tomographic reconstruction based on flexible geometric models

K. M. Hanson, G. S. Cunningham, G. R. Jennings, Jr., and D. R. Wolf

Abstract

When dealing with ill-posed inverse problems in data analysis, the Bayesian approach allows one to use prior information to guide the result toward reasonable solutions. In this work the model consists of an object whose amplitude is constant inside a flexible boundary. The flexibility of the boundary is controlled by through a distortion energy. We present an example of reconstruction of the cross section of a blood vessel from just two projections.

Keywords: maximum a posteriori (MAP) reconstruction, Bayesian estimation, warpable prior

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