Enhancing Coincidence Time Resolution of PET detectors using short-time Fourier transform and residual neural network-Reference-Cited by-同舟云学术

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Enhancing Coincidence Time Resolution of PET detectors using short-time Fourier transform and residual neural network

Published:2024-08 Issue: Volume:1065 Page:169540
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Muhashi Amanjule,Feng Xuhui^ORCID,Onishi Yuya^ORCID,Ota Ryosuke^ORCID,Liu Huafeng

Publisher

Elsevier BV

Reference32 articles.

1. Unsupervised PET logan parametric image estimation using conditional deep image prior;Cui;Med. Image Anal.,2022

2. DULDA: Dual-domain unsupervised learned descent algorithm for PET image reconstruction;Hu,2023

3. Deep dual-domain-based framework for PET image reconstruction;Gao,2024

4. Prior information-guided reconstruction network for positron emission tomography images;Liu;Quant. Imag. Med. Surg.,2023

5. Dynamic PET image reconstruction using deep physiology prior;Chen,2024

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1. An enhanced model based on deep operator network for very short-term forecasting of ship motion;Physics of Fluids;2024-08-01

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