86 citations · 150 across the 8 of their papers we have counts for
9 papers
Developing a PET/CT Foundation Model for Cross-Modal Anatomical and Functional Imaging
Yujin Oh, Robert Seifert, Yihan Cao +15
In oncology, Positron Emission Tomography-Computed Tomography (PET/CT) is widely used in cancer diagnosis, staging, and treatment monitoring, as it combines anatomical details from…
Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19
Aoxiao Zhong, Xiang Li, Dufan Wu +17
In recent years, deep learning-based image analysis methods have been widely applied in computer-aided detection, diagnosis and prognosis, and has shown its value during the public…
Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network
Nuobei Xie, Kuang Gong, Ning Guo +5
Patlak model is widely used in 18F-FDG dynamic positron emission tomography (PET) imaging, where the estimated parametric images reveal important biochemical and physiology informa…
Penalized-likelihood PET Image Reconstruction Using 3D Structural Convolutional Sparse Coding
Nuobei Xie, Kuang Gong, Ning Guo +4
Positron emission tomography (PET) is widely used for clinical diagnosis. As PET suffers from low resolution and high noise, numerous efforts try to incorporate anatomical priors i…
Multi-label Detection and Classification of Red Blood Cells in Microscopic Images
Wei Qiu, Jiaming Guo, Xiang Li +4
Cell detection and cell type classification from biomedical images play an important role for high-throughput imaging and various clinical application. While classification of sing…
Predicting Alzheimer's Disease by Hierarchical Graph Convolution from Positron Emission Tomography Imaging
Jiaming Guo, Wei Qiu, Xiang Li +3
Imaging-based early diagnosis of Alzheimer Disease (AD) has become an effective approach, especially by using nuclear medicine imaging techniques such as Positron Emission Topograp…
Network Modeling and Pathway Inference from Incomplete Data ("PathInf")
Xiang Li, Qitian Chen, Xing Wang +3
In this work, we developed a network inference method from incomplete data ("PathInf") , as massive and non-uniformly distributed missing values is a common challenge in practical…
Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network
Kuang Gong, Kyungsang Kim, Jianan Cui +4
Recently deep neural networks have been widely and successfully applied in computer vision tasks and attracted growing interests in medical imaging. One barrier for the application…
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Xiang Li, Aoxiao Zhong, Ming Lin +6
Tissue characterization has long been an important component of Computer Aided Diagnosis (CAD) systems for automatic lesion detection and further clinical planning. Motivated by th…