14 citations · 36 across the 16 of their papers we have counts for
17 papers
An Open Multi-Center Whole-Body FDG PET/CT Foundation Model for Tumor Segmentation
Xiaofeng Liu, Qianru Zhang, Thibault Marin +4
The synergistic interpretation of anatomical information from computed tomography (CT) and metabolic information from positron emission tomography (PET) is important to oncologic i…
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…
Power Battery Detection
Xiaoqi Zhao, Peiqian Cao, Chenyang Yu +10
Power batteries are essential components in electric vehicles, where internal structural defects can pose serious safety risks. We conduct a comprehensive study on a new task, powe…
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…
Dual Prompting for Diverse Count-level PET Denoising
Xiaofeng Liu, Yongsong Huang, Thibault Marin +6
The to-be-denoised positron emission tomography (PET) volumes are inherent with diverse count levels, which imposes challenges for a unified model to tackle varied cases. In this w…
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation
Jia Wei, Xiaoqi Zhao, Jonghye Woo +4
Single domain generalization (SDG) has recently attracted growing attention in medical image segmentation. One promising strategy for SDG is to leverage consistent semantic shape p…