3D Convolutional Neural Network-Based Denoising of Low-Count Whole-Body <sup>18</sup>F-Fluorodeoxyglucose and <sup>89</sup>Zr-Rituximab PET Scans

3D Convolutional Neural Network-Based Denoising of Low-Count Whole-Body <sup>18</sup>F-Fluorodeoxyglucose and <sup>89</sup>Zr-Rituximab PET Scans

Acquisition time and injected activity of <sup>18</sup>F-fluorodeoxyglucose (<sup>18</sup>F-FDG) PET should ideally be reduced. However, this decreases the signal-to-noise ratio (SNR), which impairs the diagnostic value of these PET scans. In addition, <sup>89</sup&g...

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Bibliographic Details
Main Authors: Bart M. de Vries, Sandeep S. V. Golla, Gerben J. C. Zwezerijnen, Otto S. Hoekstra, Yvonne W. S. Jauw, Marc C. Huisman, Guus A. M. S. van Dongen, Willemien C. Menke-van der Houven van Oordt, Josée J. M. Zijlstra-Baalbergen, Liesbet Mesotten, Ronald Boellaard, Maqsood Yaqub
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Diagnostics
Subjects:
low-count
CNN
denoising
<sup>18</sup>F-FDG
<sup>89</sup>Zr-antibody
Online Access:https://www.mdpi.com/2075-4418/12/3/596

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