降噪
概率逻辑
计算机科学
人工智能
非本地手段
约束(计算机辅助设计)
图像去噪
模式识别(心理学)
一致性(知识库)
噪音(视频)
图像质量
图像(数学)
视频去噪
信噪比(成像)
数学
电信
多视点视频编码
视频跟踪
对象(语法)
几何学
摘要
Due to various physical degradation factors, the signal-to-noise ratio (SNR) and image quality of PET needs further improvements. In this work, we proposed a denoising diffusion probabilistic model-based framework for PET image denoising, where the MR prior image was supplied as the additional network input, and the PET information was included in the iterative refinement steps based on Gaussian distribution assumption. 140 18F-MK- 6240 datasets were used in the evaluation, with 1/4 and 1/8 low-dose levels tested for different methods. Global and regional quantifications show that the proposed framework can outperform the Unet-based denoising and MR-guided nonlocal mean denoising methods.
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