activity
20182020
most citedDeep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19

86 citations · 95 across the 4 of their papers we have counts for

collaborators

7 papers

eess.IV202086 cited

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…

physics.med-ph20204 cited

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…

physics.med-ph20192 cited

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…

eess.IV20193 cited

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…

cs.LG2019

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…

stat.ML2018

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…