Author

F. Hashimoto

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Preprint Aug 2026

Flow Matching-Based PET Image Reconstruction

Generative models have shown strong potential for positron emission tomography (PET) image reconstruction. Although diffusion model-based reconstruction methods have demonstrated promising performance, they often require many reverse sampling steps with data-consistency updates incorporated into the sampling process. F...

F. Hashimoto, Ziqian Huang, Tatsuya Yokota et al. · 0 citations

Preprint Aug 2026

VLM- and LLM-Driven Multi-Agent System for PET Image Denoising

Positron emission tomography (PET) imaging suffers from limited spatial resolution and low signal-to-noise ratio, which can compromise quantitative accuracy and lesion detectability. Deep learning-based denoising methods have demonstrated strong potential for improving PET image quality. However, their practical deploy...

Bo-Xiao Yu, Savas Ozdemir, Y. Xing et al. · 0 citations