A Kernel Density Estimator-Based Maximum A Posteriori Image Reconstruction Method for Dynamic Emission Tomography Imaging

2016 ◽  
Vol 25 (5) ◽  
pp. 2233-2248 ◽  
Author(s):  
Alvin Ihsani ◽  
Troy H. Farncombe
Keyword(s):  
Image Reconstruction ◽  
Kernel Density ◽  
Kernel Density Estimator ◽  
Emission Tomography ◽  
Maximum A Posteriori ◽  
Density Estimator ◽  
Reconstruction Method ◽  
A Posteriori ◽  
Tomography Imaging ◽  
Image Reconstruction Method

scholarly journals Examining an image reconstruction method in infrared emission tomography

2019 ◽  
Vol 98 ◽  
pp. 266-277 ◽  
Author(s):  
Loizos Koutsantonis ◽  
Aristotelis-Nikolaos Rapsomanikis ◽  
Efstathios Stiliaris ◽  
Costas N. Papanicolas
Keyword(s):  
Image Reconstruction ◽  
Infrared Emission ◽  
Emission Tomography ◽  
Reconstruction Method ◽  
Image Reconstruction Method

scholarly journals Image reconstruction method for dual-isotope positron emission tomography

2021 ◽  
Vol 16 (01) ◽  
pp. P01035-P01035
Author(s):  
T. Fukuchi ◽  
M. Shigeta ◽  
H. Haba ◽  
D. Mori ◽  
T. Yokokita ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Image Reconstruction ◽  
Emission Tomography ◽  
Reconstruction Method ◽  
Dual Isotope ◽  
Positron Emission ◽  
Image Reconstruction Method

scholarly journals Image Reconstruction in the Positron Emission Tomography

2012 ◽  
Vol 20 ◽  
pp. 73
Author(s):  
M. Zioga ◽  
A. Nikopoulou ◽  
M. Alexandridi ◽  
D. Maintas ◽  
M. Mikeli ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Image Reconstruction ◽  
Iterative Algorithms ◽  
Nuclear Imaging ◽  
Emission Tomography ◽  
Reconstruction Method ◽  
Positron Emission ◽  
Volume Of Interest ◽  
Image Reconstruction Method

Positron Emission Tomography (PET) has become a valuable tool with a broad spectrum of clinical applications in nuclear imaging. PET scanners can collect in vivo information from positron radiotracer distributions, which is further recon- structed to a tomographic image with the help of well established analytical or iterative algorithms. In this current work, an innovative PET image reconstruction method from raw data based on a simple mathematical model is presented. The developed technique utilizes the accumulated density distribution in a predefined voxelized volume of interest. This distribution is calculated by intersecting and weighting the two-gamma annihilation line with the specified voxels. In order to test the efficiency of the new algorithm, GEANT4/GATE simulation studies were performed. In these studies, a cylindrical PET scanner was modeled and the photon interaction points are validated on an accurate physical basis. An appropriate cylin- drical phantom with different positron radiotracers was used and the reconstructed results were compared to the original phantom.

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