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Effect of Scan Time on Neuro F-18-Fluorodeoxyglucose Positron Emission Tomography Image Generated Using Deep Learning

Authors
 Kim, Jaewon  ;  Kang, Sungsik  ;  Lee, Konsu  ;  Jung, Jin Ho  ;  Kim, Garam  ;  Lim, Hyun Keong  ;  Choi, Yong  ;  Lee, Sangwon  ;  Yun, Mijin 
Citation
 JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, Vol.11(3) : 681-687, 2021-03 
Journal Title
 JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 
ISSN
 2156-7018 
Issue Date
2021-03
Keywords
Deep Learning ; PET ; Scan Time Reduction ; CNN ; Denoising ; Human Brain
Abstract
The purpose of this study was to generate the PET images with high signal-to-noise ratio (SNR) acquired for typical scan durations (H-PET) from short scan time PET images with low SNR (L-PET) using deep learning and to evaluate the effect of scan time on the quality of predicted PET image. A convolutional neural network (CNN) with a concatenated connection and residual learning framework was implemented. PET data from 27 patients were acquired for 900 s, starting 60 minutes after the intravenous administration of FDG using a commercial PET/CT scanner. To investigate the effect of scan time on the quality of the predicted H-PETs, 10 s, 30 s, 60 s, and 120 s PET data were generated by sorting the 900 s LMF data into the LMF data acquired for each scan time. Twenty-three of the 27 patient images were used for training of the proposed CNN and the remaining four patient images were used for test of the CNN. The predicted H-PETs generated by the CNN were compared to ground-truth H-PETs, L-PETS, and filtered L-PETS processed with four commonly used denoising algorithms. The peak signal-to-noise ratios (PSNRs), normalized root mean square errors (NRMSEs), and average region-of-interest (ROI) differences as a function of scan time were calculated. The quality of the predicted H-PETs generated by the CNN was superior to that of the L-PETs and filtered L-PETs. Lower NRMSEs and higher PSNRs were also obtained from predicted H-PETs compared to the L-PETS and filtered L-PETS. ROI differences in the predicted H-PETs were smaller than those of the L-PETS. The quality of the predicted H-PETs gradually improved with increasing scan times. The lowest NRMSEs, highest PSNRs, and smallest ROI differences were obtained using the predicted H-PETs for 120 s. Various performance test results for the proposed CNN indicate that it is possible to generate H-PETs from neuro FDG L-PETS using the proposed CNN method, which might allow reductions in both scan time and injection dose.
DOI
10.1166/jmihi.2021.3316
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers
Yonsei Authors
Yun, Mi Jin(윤미진) ORCID logo https://orcid.org/0000-0002-1712-163X
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/181843
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