Dinggang Shen

Research interests

Publications

• Transformers in medical image analysis

  Intelligent Medicine · 2022 · 10.1016/j.imed.2022.07.002

• A deep learning system for detecting diabetic retinopathy across the disease spectrum

  Nature Communications · 2021 · 10.1038/s41467-021-23458-5

• Lung Infection Quantification of COVID-19 in CT Images with Deep Learning

  arXiv (Cornell University) · 2020 · 10.48550/arxiv.2003.04655

• Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

  Lecture notes in computer science · 2019 · 10.1007/978-3-030-32248-9

• A Multi-Organ Nucleus Segmentation Challenge

  IEEE Transactions on Medical Imaging · 2019 · 10.1109/tmi.2019.2947628

• Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

  IEEE Transactions on Pattern Analysis and Machine Intelligence · 2018 · 10.1109/tpami.2018.2889096

• 3D conditional generative adversarial networks for high-quality PET image estimation at low dose

  NeuroImage · 2018 · 10.1016/j.neuroimage.2018.03.045

• The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development

  NeuroImage · 2018 · 10.1016/j.neuroimage.2018.03.049

• Medical Image Synthesis with Deep Convolutional Adversarial Networks

  IEEE Transactions on Biomedical Engineering · 2018 · 10.1109/tbme.2018.2814538

• Medical Image Synthesis with Context-Aware Generative Adversarial Networks

  Lecture notes in computer science · 2017 · 10.1007/978-3-319-66179-7_48

• Deep Learning in Medical Image Analysis

  Annual Review of Biomedical Engineering · 2017 · https://doi.org/10.1146/annurev-bioeng-071516-044442

• Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

  Scientific Reports · 2016 · 10.1038/srep24454

• Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

  NeuroImage · 2015 · https://doi.org/10.1016/j.neuroimage.2014.12.061

• Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis

  NeuroImage · 2014 · https://doi.org/10.1016/j.neuroimage.2014.06.077

• Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis

  Lecture notes in computer science · 2014 · 10.1007/978-3-319-10443-0_39

• Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

  Brain Structure and Function · 2013 · 10.1007/s00429-013-0687-3

• Family Poverty Affects the Rate of Human Infant Brain Growth

  PLoS ONE · 2013 · 10.1371/journal.pone.0080954

• Deep Learning-Based Feature Representation for AD/MCI Classification

  Lecture notes in computer science · 2013 · 10.1007/978-3-642-40763-5_72

• Infant Brain Atlases from Neonates to 1- and 2-Year-Olds

  PLoS ONE · 2011 · 10.1371/journal.pone.0018746

• Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease

  NeuroImage · 2011 · 10.1016/j.neuroimage.2011.09.069

• Longitudinal Development of Cortical and Subcortical Gray Matter from Birth to 2 Years

  Cerebral Cortex · 2011 · 10.1093/cercor/bhr327

• Multimodal classification of Alzheimer's disease and mild cognitive impairment

  NeuroImage · 2011 · https://doi.org/10.1016/j.neuroimage.2011.01.008

• Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects

  Proceedings of the National Academy of Sciences · 2009 · 10.1073/pnas.0811221106

• Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection

  NeuroImage · 2005 · 10.1016/j.neuroimage.2005.08.009

• Lane detection and tracking using B-Snake

  Image and Vision Computing · 2003 · 10.1016/j.imavis.2003.10.003

Current projects

No projects listed.