Jun Zhang
Orcid: 0000-0001-5579-7094Affiliations:
- Tencent AI Lab, Shenzhen, China
- Duke University, Department of Radiology, Durham, NC, USA
- University of North Carolina at Chapel Hill, Department of Radiology and the Biomedical Research Imaging Center, NC, USA (former)
- Xidian University, Xi'an, China (PhD 2014)
According to our database1,
Jun Zhang
authored at least 83 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.
Medical Image Anal., February, 2024
2023
High-Order Correlation-Guided Slide-Level Histology Retrieval With Self-Supervised Hashing.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2023
CLC-Net: Contextual and local collaborative network for lesion segmentation in diabetic retinopathy images.
Neurocomputing, March, 2023
Medical Image Anal., 2023
A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.
Medical Image Anal., 2023
Medical Image Anal., 2023
Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder Approach.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting.
CoRR, 2023
Federated contrastive learning models for prostate cancer diagnosis and Gleason grading.
CoRR, 2023
Automatic diagnosis and grading of Prostate Cancer with weakly supervised learning on whole slide images.
Comput. Biol. Medicine, 2023
Towards Real-Time Neural Video Codec for Cross-Platform Application Using Calibration Information.
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Exploring Low-Rank Property in Multiple Instance Learning for Whole Slide Image Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
RLogist: Fast Observation Strategy on Whole-Slide Images with Deep Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
DeepNoise: Signal and Noise Disentanglement Based on Classifying Fluorescent Microscopy Images via Deep Learning.
Genom. Proteom. Bioinform., October, 2022
Knowledge-Based Representation Learning for Nucleus Instance Classification From Histopathological Images.
IEEE Trans. Medical Imaging, 2022
Big-Hypergraph Factorization Neural Network for Survival Prediction From Whole Slide Image.
IEEE Trans. Image Process., 2022
PFVNet: A Partial Fingerprint Verification Network Learned From Large Fingerprint Matching.
IEEE Trans. Inf. Forensics Secur., 2022
Transformer-based unsupervised contrastive learning for histopathological image classification.
Medical Image Anal., 2022
Pan-cancer computational histopathology reveals tumor mutational burden status through weakly-supervised deep learning.
CoRR, 2022
Multi-level attention graph neural network based on co-expression gene modules for disease diagnosis and prognosis.
Bioinform., 2022
SCL-WC: Cross-Slide Contrastive Learning for Weakly-Supervised Whole-Slide Image Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Node-aligned Graph Convolutional Network for Whole-slide Image Representation and Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
IEEE Trans. Cybern., 2021
Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images.
Medical Image Anal., 2021
Proceedings of the Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis - MICCAI 2021 Challenges: MIDOG 2021, MOOD 2021, and Learn2Reg 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021
TransPath: Transformer-Based Self-supervised Learning for Histopathological Image Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Multi-modal Multi-instance Learning Using Weakly Correlated Histopathological Images and Tabular Clinical Information.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
An Interpretable Multi-Level Enhanced Graph Attention Network for Disease Diagnosis with Gene Expression Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
Minimizing Labeling Cost for Nuclei Instance Segmentation and Classification with Cross-domain Images and Weak Labels.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Weakly Supervised Deep Learning for Brain Disease Prognosis Using MRI and Incomplete Clinical Scores.
IEEE Trans. Cybern., 2020
Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI.
IEEE Trans. Pattern Anal. Mach. Intell., 2020
Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization.
Medical Image Anal., 2020
Weakly-Supervised Nucleus Segmentation Based on Point Annotations: A Coarse-to-Fine Self-Stimulated Learning Strategy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Predicting Lymph Node Metastasis Using Histopathological Images Based on Multiple Instance Learning With Deep Graph Convolution.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics.
IEEE Trans. Medical Imaging, 2019
Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.
IEEE Trans. Biomed. Eng., 2019
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ.
Comput. Biol. Medicine, 2019
Comput. Biol. Medicine, 2019
2018
Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis.
IEEE J. Biomed. Health Informatics, 2018
Weakly Supervised Semantic Segmentation for Joint Key Local Structure Localization and Classification of Aurora Image.
IEEE Trans. Geosci. Remote. Sens., 2018
IEEE Trans. Biomed. Eng., 2018
Multim. Tools Appl., 2018
Multi-task neural networks for joint hippocampus segmentation and clinical score regression.
Multim. Tools Appl., 2018
Medical Image Anal., 2018
Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images.
Medical Image Anal., 2018
Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images.
CoRR, 2018
Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Breast cancer molecular subtype classification using deep features: preliminary results.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.
IEEE J. Biomed. Health Informatics, 2017
Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks.
IEEE Trans. Image Process., 2017
IEEE Trans. Biomed. Eng., 2017
View-aligned hypergraph learning for Alzheimer's disease diagnosis with incomplete multi-modality data.
Medical Image Anal., 2017
Auroral event representation based on the n-ary fusion of multiple oriented energies.
Neurocomputing, 2017
Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
2016
IEEE Trans. Medical Imaging, 2016
Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model and Multiscale Statistical Features.
IEEE Trans. Biomed. Eng., 2016
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.
Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016
Segmentation of Perivascular Spaces Using Vascular Features and Structured Random Forest from 7T MR Image.
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Semi-supervised Hierarchical Multimodal Feature and Sample Selection for Alzheimer's Disease Diagnosis.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the 9th Eurographics Workshop on 3D Object Retrieval, 2016
2015
Automatic Craniomaxillofacial Landmark Digitization via Segmentation-Guided Partially-Joint Regression Forest Model.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Craniomaxillofacial Deformity Correction via Sparse Representation in Coherent Space.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015