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20232025
most citedDose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data

4 citations · 11 across the 12 of their papers we have counts for

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eess.IV2025

Fed-NDIF: A Noise-Embedded Federated Diffusion Model For Low-Count Whole-Body PET Denoising

Yinchi Zhou, Huidong Xie, Menghua Xia +12

Low-count positron emission tomography (LCPET) imaging can reduce patients' exposure to radiation but often suffers from increased image noise and reduced lesion detectability, nec…

eess.IV2025

Anatomically and Metabolically Informed Diffusion for Unified Denoising and Segmentation in Low-Count PET Imaging

Menghua Xia, Kuan-Yin Ko, Der-Shiun Wang +12

Positron emission tomography (PET) image denoising, along with lesion and organ segmentation, are critical steps in PET-aided diagnosis. However, existing methods typically treat t…

eess.IV2024★ 2 cited

A Generalizable 3D Diffusion Framework for Low-Dose and Few-View Cardiac SPECT

Huidong Xie, Weijie Gan, Wei Ji +13

Myocardial perfusion imaging using SPECT is widely utilized to diagnose coronary artery diseases, but image quality can be negatively affected in low-dose and few-view acquisition…

eess.IV2024

Noise-aware Dynamic Image Denoising and Positron Range Correction for Rubidium-82 Cardiac PET Imaging via Self-supervision

Huidong Xie, Liang Guo, Alexandre Velo +14

Rb-82 is a radioactive isotope widely used for cardiac PET imaging. Despite numerous benefits of 82-Rb, there are several factors that limits its image quality and quantitative acc…

eess.IV2024★ 4 cited

Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data

Huidong Xie, Weijie Gan, Reimund Bayerlein +24

Reducing scan times, radiation dose, and enhancing image quality for lower-performance scanners, are critical in low-dose PET imaging. Deep learning techniques have been investigat…

eess.IV2024★ 1 cited

LeqMod: Adaptable Lesion-Quantification-Consistent Modulation for Deep Learning Low-Count PET Image Denoising

Menghua Xia, Huidong Xie, Qiong Liu +9

Deep learning-based positron emission tomography (PET) image denoising offers the potential to reduce radiation exposure and scanning time by transforming low-count images into hig…

eess.IV2024

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction

Xueqi Guo, Luyao Shi, Xiongchao Chen +11

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82-Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification a…

eess.IV2024

Dual-Domain Coarse-to-Fine Progressive Estimation Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT

Xiongchao Chen, Bo Zhou, Xueqi Guo +5

Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but lead…

eess.IV2023★ 2 cited

DDPET-3D: Dose-aware Diffusion Model for 3D Ultra Low-dose PET Imaging

Huidong Xie, Weijie Gan, Bo Zhou +8

As PET imaging is accompanied by substantial radiation exposure and cancer risk, reducing radiation dose in PET scans is an important topic. Recently, diffusion models have emerged…

eess.IV2023

FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising

Bo Zhou, Huidong Xie, Qiong Liu +10

Low-count PET is an efficient way to reduce radiation exposure and acquisition time, but the reconstructed images often suffer from low signal-to-noise ratio (SNR), thus affecting…