Shandong Wu

Orcid: 0000-0002-0770-2203

According to our database1, Shandong Wu authored at least 62 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis.
IEEE Trans. Cybern., April, 2024

Longitudinal Mammogram Exam-based Breast Cancer Diagnosis Models: Vulnerability to Adversarial Attacks.
CoRR, 2024

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models.
CoRR, 2024

Adversarially Robust Feature Learning for Breast Cancer Diagnosis.
CoRR, 2024

Knowledge-Guided Multi-Task Learning for Breast Cancer Diagnosis Using Longitudinal Mammogram Images.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Medical Knowledge-Enabled Multi-Task Learning for Gastric Cancer Survival Prediction.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning.
Trans. Mach. Learn. Res., 2023

Medical knowledge-guided deep learning for mammographic breast density classification.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Anterior cruciate ligament classification in knee MRI using automated pseudo-masking.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Human Not in the Loop: Objective Sample Difficulty Measures for Curriculum Learning.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

PGFed: Personalize Each Client's Global Objective for Federated Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Deep learning of longitudinal mammogram examinations for breast cancer risk prediction.
Pattern Recognit., 2022

Cross-Domain Self-Supervised Deep Learning for Robust Alzheimer's Disease Progression Modeling.
CoRR, 2022

SurvivalCNN: A deep learning-based method for gastric cancer survival prediction using radiological imaging data and clinicopathological variables.
Artif. Intell. Medicine, 2022

A self-training teacher-student model with an automatic label grader for abdominal skeletal muscle segmentation.
Artif. Intell. Medicine, 2022

Incorporate radiograph-reading behavior and knowledge into deep reinforcement learning for lesion localization.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

Deep curriculum learning in task space for multi-class based mammography diagnosis.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

Fedsld: Federated Learning with Shared Label Distribution for Medical Image Classification.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
3D Context-Aware Convolutional Neural Network for False Positive Reduction in Clustered Microcalcifications Detection.
IEEE J. Biomed. Health Informatics, 2021

Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification.
CoRR, 2021

Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images.
CoRR, 2021

Disentangled and Proportional Representation Learning for Multi-view Brain Connectomes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Radiomics-Informed Deep Curriculum Learning for Breast Cancer Diagnosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture Classification.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Multi-task learning to incorporate clinical knowledge into deep learning for breast cancer diagnosis.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Medical knowledge-guided deep curriculum learning for elbow fracture diagnosis from x-ray images.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2020
Guest Editorial: Deep Learning in Ultrasound Imaging.
IEEE J. Biomed. Health Informatics, 2020

Inaccurate Labels in Weakly-Supervised Deep Learning: Automatic Identification and Correction and Their Impact on Classification Performance.
IEEE J. Biomed. Health Informatics, 2020

Deep Convolutional Radiomic Features on Diffusion Tensor Images for Classification of Glioma Grades.
J. Digit. Imaging, 2020

Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics.
J. Digit. Imaging, 2020

Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study.
J. Digit. Imaging, 2020

Response score of deep learning for out-of-distribution sample detection of medical images.
J. Biomed. Informatics, 2020

Handling imbalanced medical image data: A deep-learning-based one-class classification approach.
Artif. Intell. Medicine, 2020

Performance comparison of different loss functions for digital breast tomosynthesis classification using 3D deep learning model.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Object tracking based on Huber loss function.
Vis. Comput., 2019

Robust UAV-based tracking using hybrid classifiers.
Mach. Vis. Appl., 2019

Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRI.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk prediction.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategy.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2018
Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective.
J. Digit. Imaging, 2018

Do pre-trained deep learning models improve computer-aided classification of digital mammograms?
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2015
Visual tracking based on group sparsity learning.
Mach. Vis. Appl., 2015

Signal enhancement ratio (SER) quantified from breast DCE-MRI and breast cancer risk.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

2013
Tumor segmentation in brain MRI by sparse optimization.
Proceedings of the Medical Imaging 2013: Image Processing, 2013

Fully-automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI by integrating a continuous max-flow model and a likelihood atlas.
Proceedings of the Medical Imaging 2013: Computer-Aided Diagnosis, 2013

2012
Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Fully automated chest wall line segmentation in breast MRI by using context information.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, San Diego, 2012

Fully-Automated Fibroglandular Tissue Segmentation in Breast MRI.
Proceedings of the Breast Imaging, 2012

2011
Action recognition in videos acquired by a moving camera using motion decomposition of Lagrangian particle trajectories.
Proceedings of the IEEE International Conference on Computer Vision, 2011

2010
Motion trajectory reproduction from generalized signature description.
Pattern Recognit., 2010

Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Flexible signature descriptions for adaptive motion trajectory representation, perception and recognition.
Pattern Recognit., 2009

Probabilistic Cluster Signature for Modeling Motion Classes.
Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

2008
On Signature Invariants for Effective Motion Trajectory Recognition.
Int. J. Robotics Res., 2008

Signature based task description and perception for motion trajectory priented Robot Learning.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2008

Invariant signature description and trajectory reproduction for robot Learning by Demonstration.
Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008

A hierarchical motion trajectory signature descriptor.
Proceedings of the 2008 IEEE International Conference on Robotics and Automation, 2008

2007
A viewpoint invariant signature descriptor for curved shape recognition.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2007

2004
Miam: A Robot Oriented Mobile Intelligent Agent Model.
Proceedings of the Intelligent Information Processing II, 2004

Remote Robot Control Using Intelligent Hand-Held Devices.
Proceedings of the 2004 International Conference on Computer and Information Technology (CIT 2004), 2004


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