In this paper, the authors review the field of resolution modeling in positron emission
tomography (PET) image reconstruction, also referred to as point‐spread‐function modeling …

In emission tomography statistically based iterative methods can improve image quality
relative to analytic image reconstruction through more accurate physical and statistical …

Recently, deep neural networks have been widely and successfully applied in computer
vision tasks and have attracted growing interest in medical imaging. One barrier for the …

PET image reconstruction is challenging due to the ill-poseness of the inverse problem and
limited number of detected photons. Recently, the deep neural networks have been widely …

Amide's a Medical Image Data Examiner (AMIDE) has been developed as a user-friendly,
open-source software tool for displaying and analyzing multimodality volumetric medical …

Purpose: The aim of this work was the assessment of the physical performance of the new
hybrid PET/CT system: Discovery‐690. Methods: The Discovery‐690 combines a lutetium …

We have constructed a three-dimensional (3D) whole body mouse atlas from coregistered x-
ray CT and cryosection data of a normal nude male mouse. High quality PET, x-ray CT and …

The quality of images reconstructed by statistical iterative methods depends on an accurate
model of the relationship between image space and projection space through the system …

introduced. The methods by which PET data are reconstructed into a three-dimensional
image volume are explained, along with some of the approaches that are used to analyze …

Machine learning has found unique applications in nuclear medicine from photon detection
to quantitative image reconstruction. Although there have been impressive strides in …