Positron Emission Tomography Image Reconstruction Method Utilizing Magnetic Resonance Image.

Maximum Likelihood Algorithms for Image Reconstruction in Positron Emission Tomography

Penalized weighted least-squares image reconstruction for positron emission tomography

Presents an image reconstruction method for positron-emission tomography (PET) based on a penalized, weighted least-squares (PWLS) objective. For PET measurements that are precorrected for accidental coincidences, the author argues statistically that a least-squares objective function is as appropriate, if not more so, than the popular Poisson likelihood objective. The author proposes a simple ...

A New Algorithm for Image Reconstruction for Positron Emission Tomography

In Positron Emission Tomography, penalized iterative algorithms like MAP often results in over smooth reconstructions due to over penalizing nature of the assumed interacting potential. These algorithms fail to determine the density class of the estimate and hence penalize the pixels irrespective of the density class. In this work, a fuzzy logic based approach is proposed to model the prior whi...

Characteristics of Smoothing Filters to Achieve the Guideline Recommended Positron Emission Tomography Image without Harmonization

Objective(s): The aim of this study is to examine the effect of different smoothing filters on the image quality and SUVmax to achieve the guideline recommended positron emission tomography (PET) image without harmonization. Methods: We used a Biograph mCT PET scanner. A National Electrical Manufacturers Association (NEMA) the International Electrotechnical Commission (IEC) body phantom was fil...

Positron Emission Tomography-Computed Tomography Data Acquisition and Image Management