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Bayesian imagereconstruction inSPECT using higherorder mechanicalmodels as priors Soo‐Jin LeeAnand RangarajanGene Gindi1995 год

Bayesian image reconstruction in SPECT using higher order mechanical models as priors
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Аннотация: While the ML-EM algorithm for reconstruction for emission tomography is unstable due to the ill-posed nature of the problem. Bayesian reconstruction methods overcome this instability by introducing prior information, often in the form of a spatial smoothness regularizer. More elaborate forms of smoothness constraints may be used to extend the role of the prior beyond that of a stabilizer in order to capture actual spatial information about the object. Previously proposed forms of such prior distributions were based on the assumption of a piecewise constant source distribution. Here, the authors propose an extension to a piecewise linear model-the weak plate-which is more expressive than the piecewise constant model. The weak plate prior not only preserves edges but also allows for piecewise ramplike regions in the reconstruction. Indeed, for the authors' application in SPECT, such ramplike regions are observed in ground-truth source distributions in the form of primate autoradiographs of rCBF radionuclides. To incorporate the weak plate prior in a MAP approach, the authors model the prior as a Gibbs distribution and use a GEM formulation for the optimization. They compare quantitative performance of the ML-EM algorithm, a GEM algorithm with a prior favoring piecewise constant regions, and a GEM algorithm with their weak plate prior. Pointwise and regional bias and variance of ensemble image reconstructions are used as indications of image quality. The authors' results show that the weak plate and membrane priors exhibit improved bias and variance relative to ML-EM techniques.
Год издания: 1995
Авторы: Soo‐Jin Lee, Anand Rangarajan, Gene Gindi
Издательство: Institute of Electrical and Electronics Engineers
Источник: IEEE Transactions on Medical Imaging
Ключевые слова: Medical Imaging Techniques and Applications, Advanced MRI Techniques and Applications, Radiation Detection and Scintillator Technologies
Другие ссылки: IEEE Transactions on Medical Imaging (HTML)
PubMed (HTML)