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arXiv · 2404.01563

Two-Phase Multi-Dose-Level PET Image Reconstruction with Dose Level Awareness

Yuchen Fei·Yanmei Luo·Yan Wang·Jiaqi Cui·Yuanyuan Xu·Jiliu Zhou·Dinggang Shen
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Abstract

To obtain high-quality positron emission tomography (PET) while minimizing radiation exposure, a range of methods have been designed to reconstruct standard-dose PET (SPET) from corresponding low-dose PET (LPET) images. However, most current methods merely learn the mapping between single-dose-level LPET and SPET images, but omit the dose disparity of LPET images in clinical scenarios. 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. Specifically, the pre-training phase is devised to explore both fine-grained discriminative features and effective semantic representation. The SPET prediction phase adopts a coarse prediction network utilizing pre-learned dose level prior to generate preliminary result, and a refinement network to precisely preserve the details. Experiments on MICCAI 2022 Ultra-low Dose PET Imaging Challenge Dataset have demonstrated the superiority of our method.

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Yuchen Fei, Yanmei Luo, Yan Wang, Jiaqi Cui, Yuanyuan Xu, Jiliu Zhou, Dinggang Shen. 2024-04-02. Two-Phase Multi-Dose-Level PET Image Reconstruction with Dose Level Awareness. https://arxiv.org/abs/2404.01563

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