Medical Imaging
Multiple modality medical data for brain disorder diagnosis

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Daniel Kaufer, Guorong Wu,

Dynamic Hyper-Graph Inference Framework for Computer-Assisted Diagnosis of Neurodegenerative Diseases,

IEEE Transaction on Medical Imaging, 2018.


Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, GuorongWu,

A Novel Dynamic Hyper-Graph Inference Framework for Computer-Assisted Diagnosis of Neuro-Diseases,

International Conference on Information Processing in Medical Imaging (IPMI)​ 2017.​

Zhengxia Wang, Xiaofeng Zhu, Yingying Zhu, Minjeong Kim, Daniel Kaufer and Guorong Wu,

Multi-Modal Classification of Neurodegenerative Disease by Progressive Graph-Based Transductive Learning,

Medical Image Analysis, 2017.​

Dynamic Brain Connectomics and Its Applications

Yingying Zhu, Daniel Kaufer and GuorongWu,

A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity,

International Conference on Information Processing in Medical Imaging (IPMI) , 2017.

 

Yingying Zhu, Xiaofeng Zhu, Han Zhang, Wei Gao, Dinggang Shen, and GuorongWu, 

Reveal the brain connectivity dynamics for the Autism identification using fMRI Images, 

Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2016.

 

Fatemeh Mokhtari, Walter J Rejeski, Yingying Zhu, Guorong Wu, Sean L Simpson, Jonathan H Burdette,

Dynamic fMRI Networks Predict Success in a Behavioral Weight Loss Program among Older Adults,

NeuroImage, 2018.

Early Alzheimer's diagnosis using longitudinal MR Images

Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, and Guorong Wu,

Early Detection of Alzheimer’s Disease by Jointly Feature Selection and Structural Support Vector Machine,

Medical Image Computing and Computer-Assisted Intervention (MICCAI) ,2016, Oral, accept rate < 4.5%

 

Yingying Zhu, Minjeong Kim, Xiaofeng Zhu and Guorong Wu,

Long Range Early Diagnosis of AD using Longitudinal MR Images,

under revision with Medical Image Analysis.

Personalized Diagnosis Model for Neuro-degegernative Diseases

YingyingZhu, Minjeong Kim, Daniel Kaufer and Guorong Wu,

Personalized Diagnosis Model for brain disorders,

Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2017.

Predicting Future Clinical Outcome for Progressive Diseases

Yingying Zhu, Mert R. Sabuncu,

A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome,

Medical Image Computing and Computer-Assisted Intervention (MICCAI) workshop 2018.

 

Yingying Zhu, Mert R. Sabuncu,

A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome,

submitted to Transaction on Big Data.

 

Yingying Zhu, Mert R. Sabuncu, 

A Bayesian Model for Non-invasive Prediction of Clinical Trajectories in Alzheimer’s Disease,

submitted to Alzhermier's and Dementia.

Computer Vision
Complex Non-Rigid Motion Reconstruction

Yingying Zhu, Fernando De La Torre, and Simon Lucey,

Complex Nonrigid Motion 3D Reconstruction by Union of Subspaces,

Conference on Computer Vision and Pattern Recognition (CVPR), 2014.

3D  Motion Trajectory Reconstruction by Sparse Coding

Yingying Zhu, Simon Lucey,

Convolutional Sparse Coded Filters Nonrigid Structure From Motion,

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015.

Yingying Zhu, Jack Valmadre and Simon Lucey,

Camera-less Articulated Trajectory Reconstruction,

 International Conference on Pattern Recognition (ICPR), 2012.

Jack Valmadre, Yingying Zhu and Simon Lucey,

Dynamic Filter Articulated Structure Motion Reconstruction,

 European Conference on Computer Vision (ECCV), 2012.

Real-world Camera Non-rigid Structure From Motion

Yingying Zhu, Mark Cox and Simon Lucey,

3D Motion Reconstruction for Real-World Camera Motion,

Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

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