Bayesian image reconstruction for transmission tomography using mixture model priors and deterministic annealing algorithms

Ing-Tsung Hsiao; Anand Rangarajan; Gene R. Gindi

doi:10.1117/12.431169

3 July 2001 Bayesian image reconstruction for transmission tomography using mixture model priors and deterministic annealing algorithms

Ing-Tsung Hsiao, Anand Rangarajan, Gene R. Gindi

Author Affiliations +

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431169
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

We previously introduced a new Bayesian reconstruction method for transmission tomographic reconstruction that is useful in attenuation correction in SPECT and PET. To make it practical, we apply a deterministic annealing algorithm to the method in order to avoid the dependence of the MAP estimate on the initial conditions. The Bayesian reconstruction method used a novel pointwise prior in the form of a mixture of gamma distributions. The prior models the object as comprising voxels whose values (attenuation coefficients) cluster into a few classes (e.g. soft tissue, lung, bone). This model is particularly applicable to transmission tomography since the attenuation map is usually well-clustered and the approximate values of attenuation coefficients in each region are known. The algorithm is implemented as two alternating procedures, a regularized likelihood reconstruction and a mixture parameter estimation. The Bayesian reconstruction algorithm can be effective, but has the problem of sensitivity to initial conditions since the overall objective is non-convex. To make it more practical, it is important to avoid such dependence on initial conditions. Here, we implement a deterministic annealing (DA) procedure on the alternating algorithm. We present the Bayesian reconstructions with/out DA and show the independence of initial conditions with DA.

Citation Download Citation

Ing-Tsung Hsiao, Anand Rangarajan, and Gene R. Gindi "Bayesian image reconstruction for transmission tomography using mixture model priors and deterministic annealing algorithms", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431169

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