4 citations · 10 across the 10 of their papers we have counts for
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Unsupervised Adaptation from FDG to PSMA PET/CT for 3D Lesion Detection under Label Shift
Xiaofeng Liu, Menghua Xia, Yanis Chemli +3
In this work, we propose an unsupervised domain adaptation (UDA) framework for 3D volumetric lesion detection that adapts a detector trained on labeled FDG PET/CT to unlabeled PSMA…
On hallucinations in AI-generated content for nuclear medicine imaging (the DREAM report)
Menghua Xia, Reimund Bayerlein, Yanis Chemli +7
Artificial intelligence-generated content (AIGC) has shown remarkable performance in nuclear medicine imaging (NMI), offering cost-effective software solutions for tasks such as im…
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…
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…
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…
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…
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…
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…