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Found 4 papers, 1 papers with code
Two-Phase Multi-Dose-Level PET Image Reconstruction with Dose Level Awareness
In this paper, to reconstruct high-quality SPET images from multi-dose-level LPET images, we design a novel two-phase multi-dose-level PET reconstruction algorithm with dose level awareness, containing a pre-training phase and a SPET prediction phase.
Dose Prediction Driven Radiotherapy Paramters Regression via Intra- and Inter-Relation Modeling
Deep learning has facilitated the automation of radiotherapy by predicting accurate dose distribution maps.
Image2Points:A 3D Point-based Context Clusters GAN for High-Quality PET Image Reconstruction
To obtain high-quality Positron emission tomography (PET) images while minimizing radiation exposure, numerous methods have been proposed to reconstruct standard-dose PET (SPET) images from the corresponding low-dose PET (LPET) images.
TriDo-Former: A Triple-Domain Transformer for Direct PET Reconstruction from Low-Dose Sinograms
Specifically, the TriDo-Former consists of two cascaded networks, i. e., a sinogram enhancement transformer (SE-Former) for denoising the input LPET sinograms and a spatial-spectral reconstruction transformer (SSR-Former) for reconstructing SPET images from the denoised sinograms.
