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Signal separation of simultaneous dual-tracer PET imaging based on global spatial information and channel attention.
- Source :
-
EJNMMI Physics . 5/29/2024, Vol. 11 Issue 1, p1-19. 19p. - Publication Year :
- 2024
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Abstract
- Background: Simultaneous dual-tracer positron emission tomography (PET) imaging efficiently provides more complete information for disease diagnosis. The signal separation has long been a challenge of dual-tracer PET imaging. To predict the single-tracer images, we proposed a separation network based on global spatial information and channel attention, and connected it to FBP-Net to form the FBPnet-Sep model. Results: Experiments using simulated dynamic PET data were conducted to: (1) compare the proposed FBPnet-Sep model to Sep-FBPnet model and currently existing Multi-task CNN, (2) verify the effectiveness of modules incorporated in FBPnet-Sep model, (3) investigate the generalization of FBPnet-Sep model to low-dose data, and (4) investigate the application of FBPnet-Sep model to multiple tracer combinations with decay corrections. Compared to the Sep-FBPnet model and Multi-task CNN, the FBPnet-Sep model reconstructed single-tracer images with higher structural similarity, peak signal-to-noise ratio and lower mean squared error, and reconstructed time-activity curves with lower bias and variation in most regions. Excluding the Inception or channel attention module resulted in degraded image qualities. The FBPnet-Sep model showed acceptable performance when applied to low-dose data. Additionally, it could deal with multiple tracer combinations. The qualities of predicted images, as well as the accuracy of derived time-activity curves and macro-parameters were slightly improved by incorporating a decay correction module. Conclusions: The proposed FBPnet-Sep model was considered a potential method for the reconstruction and signal separation of simultaneous dual-tracer PET imaging. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21977364
- Volume :
- 11
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- EJNMMI Physics
- Publication Type :
- Academic Journal
- Accession number :
- 177559496
- Full Text :
- https://doi.org/10.1186/s40658-024-00649-9