This website uses cookies.
We use cookies to improve your online experience. By continuing to use our website we assume you agree to the placement of these cookies.
To learn more, you can find in our Privacy Policy.
Original paper

DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms

Volume: 245, Pages: 118697 - 118697
Published: Nov 3, 2021
Abstract
Reducing the injected activity and/or the scanning time is a desirable goal to minimize radiation exposure and maximize patients' comfort. To achieve this goal, we developed a deep neural network (DNN) model for synthesizing full-dose (FD) time-of-flight (TOF) bin sinograms from their corresponding fast/low-dose (LD) TOF bin sinograms. Clinical brain PET/CT raw data of 140 normal and abnormal patients were employed to create LD and FD TOF bin...
Paper Details
Title
DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms
Published Date
Nov 3, 2021
Journal
Volume
245
Pages
118697 - 118697
© 2025 Pluto Labs All rights reserved.
Step 1. Scroll down for details & analytics related to the paper.
Discover a range of citation analytics, paper references, a list of cited papers, and more.