Multimodal feature‐guided diffusion model for low‐count PET image denoising

To minimize radiation exposure while obtaining high‐quality Positron Emission Tomography (PET) images, various methods have been developed to derive standard‐count PET (SPET) images from low‐count PET (LPET) images. Although deep learning methods have enhanced LPET images, they rarely utilize the rich complementary information from MR images. Even when MR images are used, these methods typically employ early, intermediate, or late fusion strategies to merge features from different CNN streams, failing to fully exploit the complementary properties of multimodal fusion.

• Publication year

  2025

• Venue

  Medical Physics (Lancaster)

• Publication date

  2025-03-18

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1002/mp.17764PMID 40102174
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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