Hua Li
Orcid: 0000-0002-5629-2247Affiliations:
- University of Illinois at Urbana-Champaign, Department of Bioengineering, Cancer Center, Urbana, IL, USA
- Washington University, Department of Radiation Oncology, St. Louis, MO, USA (former)
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, MN, USA (former)
- Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA (former)
- CNRS UMR, GREYC-ENSICAEN, Caen, France (former)
- Huazhong University of Science and Technology, Department of Electronics and Information Engineering, Wuhan, China (PhD 2001)
According to our database1,
Hua Li
authored at least 58 papers
between 2004 and 2025.
Collaborative distances:
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Bibliography
2025
Generation of super-resolution for medical image via a self-prior guided Mamba network with edge-aware constraint.
Pattern Recognit. Lett., 2025
2024
Assessing the Capacity of a Denoising Diffusion Probabilistic Model to Reproduce Spatial Context.
IEEE Trans. Medical Imaging, October, 2024
CoRR, 2024
2023
Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework.
Medical Image Anal., December, 2023
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
An auxiliary attention-based network for joint classification and localization of breast tumor on ultrasound images.
Proceedings of the Medical Imaging 2023: Image Processing, 2023
Deep-supervised adversarial learning-based classification for digital histologic images.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023
Semi-supervised contrastive learning for white blood cell segmentation from label-free quantitative phase imaging.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023
Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy.
Proceedings of the Twelfth International Conference on Image Processing Theory, 2023
2022
A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.
IEEE Trans. Medical Imaging, 2022
Joint localization and classification of breast tumors on ultrasound images using a novel auxiliary attention-based framework.
CoRR, 2022
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Processing, 2022
2021
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks.
IEEE Trans. Medical Imaging, 2021
Deeply-supervised density regression for automatic cell counting in microscopy images.
Medical Image Anal., 2021
Multi-Label Active Learning Algorithms for Image Classification: Overview and Future Promise.
ACM Comput. Surv., 2021
CoRR, 2021
Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs.
CoRR, 2021
A novel systematic approach for cancer treatment prognosis and its applications in oropharyngeal cancer with microRNA biomarkers.
Bioinform., 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Supervised learning-based ideal observer approximation for joint detection and estimation tasks.
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Proceedings of the Medical Imaging 2021: Image-Guided Procedures, 2021
2020
Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods.
IEEE Trans. Medical Imaging, 2020
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs.
CoRR, 2020
Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation.
Comput. Biol. Medicine, 2020
Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements.
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Deep Disentangled Representation Learning of Pet Images for Lymphoma Outcome Prediction.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
2019
Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods.
IEEE Trans. Medical Imaging, 2019
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions.
IEEE Trans. Image Process., 2019
Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy.
Int. J. Comput. Assist. Radiol. Surg., 2019
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods.
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Automatic microscopic cell counting by use of deeply-supervised density regression model.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019
2018
Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images.
IEEE Trans. Biomed. Eng., 2018
A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.
Medical Image Anal., 2018
Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images.
CoRR, 2018
Convolutional neural network based automatic plaque characterization for intracoronary optical coherence tomography images.
Proceedings of the Medical Imaging 2018: Image Processing, 2018
Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2017
Proceedings of the 2017 ACM on Multimedia Conference, 2017
Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2016
Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
2015
Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
2009
3D Multi-branch Tubular Surface and Centerline Extraction with 4D Iterative Key Points.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009
2007
Vessels as 4-D Curves: Global Minimal 4-D Paths to Extract 3-D Tubular Surfaces and Centerlines.
IEEE Trans. Medical Imaging, 2007
IEEE Trans. Pattern Anal. Mach. Intell., 2007
2006
3D Brain Segmentation Using Dual-Front Active Contours with Optional User Interaction.
Int. J. Biomed. Imaging, 2006
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006
2005
Proceedings of the 2005 International Conference on Image Processing, 2005
Fast 3D Brain Segmentation Using Dual-Front Active Contours with Optional User-Interaction.
Proceedings of the Computer Vision for Biomedical Image Applications, 2005
2004
Proceedings of the Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004, 2004
Proceedings of the 17th International Conference on Pattern Recognition, 2004
Proceedings of the 2004 International Conference on Image Processing, 2004