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Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network


Jul 12, 2021
Bo Zhou, Rui Wang, Ming-Kai Chen, Adam P. Mecca, Ryan S. O'Dell, Christopher H. Van Dyck, Richard E. Carson, James S. Duncan, Chi Liu

* Accepted at MICCAI 2021 

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Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth


Jul 12, 2021
Bo Zhou, Chi Liu, James S. Duncan

* Accepted at MICCAI 2021 

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Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation


May 14, 2021
Chenyu You, Ruihan Zhao, Lawrence Staib, James S. Duncan


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Estimating Reproducible Functional Networks Associated with Task Dynamics using Unsupervised LSTMs


May 06, 2021
Nicha C. Dvornek, Pamela Ventola, James S. Duncan

* 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020, p. 1395-1398 
* IEEE International Symposium on Biomedical Imaging (ISBI) 2020 

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Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity


Apr 15, 2021
Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, Pamela Ventola, James S. Duncan

* MLMI 2020 (MICCAI Workshop) 

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Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration


Apr 14, 2021
Bo Zhou, Zachary Augenfeld, Julius Chapiro, S. Kevin Zhou, Chi Liu, James S. Duncan

* 12 pages, 8 figures, published at Medical Image Analysis (MedIA), code available at https://github.com/bbbbbbzhou/APA2Seg-Net 

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MALI: A memory efficient and reverse accurate integrator for Neural ODEs


Mar 03, 2021
Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan

* International Conference on Learning Representation, ICLR 2021 
* https://openreview.net/forum?id=blfSjHeFM_e 

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AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients


Oct 24, 2020
Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar Tatikonda, Nicha Dvornek, Xenophon Papademetris, James S. Duncan

* NeurIPS 2020 

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Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation


Sep 06, 2020
Chenyu You, Junlin Yang, Julius Chapiro, James S. Duncan


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Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency


Sep 03, 2020
Bo Zhou, S. Kevin Zhou, James S. Duncan, Chi Liu

* Submitted to the IEEE for possible publication 

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A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises


Aug 02, 2020
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers

* 19 pages, 7 figures 

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Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results


Jan 16, 2020
Xiaoxiao Li, Yufeng Gu, Nicha Dvornek, Lawrence Staib, Pamela Ventola, James S. Duncan

* 12 pagers, 11 figures, preprint submitted to Medical Image Analysis 

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Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making


Dec 01, 2019
Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, MingDe Lin, Aaron Abajian, James S. Duncan

* Accepted by NeurIPS workshop MED-NeurIPS 2019 

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Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI


Oct 15, 2019
Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, James S. Duncan

* 10th International Workshop on Machine Learning in Medical Imaging (MLMI 2019) 

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Decision Explanation and Feature Importance for Invertible Networks


Oct 15, 2019
Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Junlin Yang, James S. Duncan

* ICCVW 2019 
* Correct notations 

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Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation


Aug 29, 2019
Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, MingDe Lin, James S. Duncan


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Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation


Aug 27, 2019
Junlin Yang, Nicha C. Dvornek, Fan Zhang, Juntang Zhuang, Julius Chapiro, MingDe Lin, James S. Duncan


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Invertible Network for Classification and Biomarker Selection for ASD


Jul 23, 2019
Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan


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Graph Neural Network for Interpreting Task-fMRI Biomarkers


Jul 12, 2019
Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan

* Medical Image Computing and Computer-Assisted Intervention 2019 

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Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery


Dec 14, 2018
Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan

* 13 pages, 7 figures, under review 

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Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI


Aug 23, 2018
Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan

* 8 pagers, accepted by MICCAI 2018 

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Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation


Jul 12, 2018
Allen Lu, Nripesh Parajuli, Maria Zontak, John Stendahl, Kevinminh Ta, Zhao Liu, Nabil Boutagy, Geng-Shi Jeng, Imran Alkhalil, Lawrence H. Staib, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan


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Flow Network Tracking for Spatiotemporal and Periodic Point Matching: Applied to Cardiac Motion Analysis


Jul 09, 2018
Nripesh Parajuli, Allen Lu, Kevinminh Ta, John C. Stendahl, Nabil Boutagy, Imran Alkhalil, Melissa Eberle, Geng-Shi Jeng, Maria Zontak, Matthew ODonnell, Albert J. Sinusas, James S. Duncan

* Submitted manuscript to Medical Image Analysis Journal 

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Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging


May 24, 2018
Nicha C. Dvornek, Daniel Yang, Archana Venkataraman, Pamela Ventola, Lawrence H. Staib, Kevin A. Pelphrey, James S. Duncan

* Multimodal Learning for Clinical Decision Support (ML-CDS) 2016 

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