Publications

Selected Journal Articles:

Selected Conference Proceedings:

  • Kaiyan Li, Weimin Zhou, Hua Li*, Mark Anastasio*, “Estimating task-based performance bounds for image reconstruction methods by use of learned-Ideal Observers”, SPIE Medical Imaging Conference Proceedings, 2023
  • Zhimin Wang, Zong Fan, Lulu Sun, Xiaowei Wang, Hua Li*, “Deep-supervised multiclass classification by use of digital histopathology images”, SPIE Medical Imaging Conference Proceedings, 2023
  • Zong Fan, Ping Gong, Shanshan Tang, Christine U. Lee, Xiaohui Zhang, Zhimin Wang, Shigao Chen, Pengfei Song, Hua Li*. “An auxiliary attention-based network for joint classification and localization of breast tumor on ultrasound images”. SPIE Medical Imaging Conference Proceedings, 2023.
  • Kaiyan Li, Hua Li, Mark Anastasio. “A task-informed model training method for deep neural network-based image denoising.” In Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment, vol. 12035, pp. 249-255. SPIE, 2022.
  • Zong Fan, Varun Kelkar, Mark A. Anastasio, Hua Li*, “Application of DatasetGAN in medical imaging: preliminary studies,” Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 120321O (4 April 2022); https://doi.org/10.1117/12.2611191
  • Zong Fan, Shenghua He, Su Ruan, Xiaowei Wang, Hua Li, “Deep learning-based multi-class COVID-19 classification with x-ray images,” SPIE Medical Imaging Conference Proceedings, 2021, Oral presentation.
  • Shenghua He, Weimin Zhou, Hua Li*, Mark Anastasio, “Learning numerical observers using unsupervised domain adaptation”, SPIE Medical Imaging Conference Proceedings, 2020, Oral presentation.
  • Weimin Zhou, Sayantan Bhadra, Frank Brooks, Hua Li, Mark Anastasio, “Progressively growing AmbientGANs for learning stochastic object models from noisy imaging measurements,”, SPIE Medical Imaging Conference Proceedings, 2020, Oral presentation.
  • Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark Anastasio, Hua Li*, “Automatic Microscopic Cell Counting by Use of Deeply-Supervised Density Regression Model”, SPIE Medical Imaging Conference Proceedings, 2019, Oral presentation.
  • Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark Anastasio, “Automatic Microscopic Cell Counting by Use of Unsupervised Adversarial Domain Adaptation and Supervised Density Regression”, SPIE Medical Imaging Conference Proceedings, 2019, Oral presentation.
  • Weimin Zhou, Hua Li, Mark Anastasio, “Learning the Hoteling observer for SKE detection tasks by use of supervised learning methods”, SPIE Medical Imaging Conference Proceedings, 2019, Oral presentation.
  • Jian Wu, Su Ruan, Thomas Mazur, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Chunfeng Lian, H. Michael Gach, Sasa Mutic, Maria Thomas, Mark Anastasio, Hua Li*, “Heart Motion Tracking on Cine MRI Based on a Deep Boltzmann Machine-Driven Level Set Method”, 2018 IEEE International Symposium on Biomedical Imaging (ISBI’2018), Washington D.C, 2018.
  • Shenghua He, Mark Anastasio, Hua Li*, “CNN-based automatic plaque characterization for intracoronary optical coherence tomography images”, SPIE Medical Imaging Conference Proceedings, 2018.
  • Jian Wu, Su Ruan, Hua Li*, “Active Learning with Noise Modeling for Medical Image Annotation”, 2018 IEEE International Symposium on Biomedical Imaging (ISBI’2018), Washington D.C, 2018.
  • Chunfeng Lian, Hua Li, Pierre Vera, Su Ruan, “Unsupervised Co-Segmentation of Tumor in PET-CT Images Using Belief Functions Based Fusion”, 2018 IEEE International Symposium on Biomedical Imaging (ISBI’2018), Washington D.C, 2018.
  • Jian Wu, Anqian Guo, Victor S. Sheng, Pengpeng Zhao, Zhiming Cui, Hua Li*, “Adaptive Low-Rank Multi-Label Active Learning for Image Classification”, ACM Multimedia 2017, Oct. 23-27, 2017, Mountain View, CA USA. doi: 10.1145/3123266.3123388.
  • Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera, “Tumor Delineation in FDG-PET Images using a new Evidential Clustering Algorithm with Spatial Regularization and Adaptive Distance Metric”, International Symposium on Biomedical Imaging (ISBI’2017), 2017. doi: 10.1109/ISBI.2017.7950726.
  • Steven Dolly, Mark Anastasio, Hua Li*, “Task-Based Image Quality Assessment in Radiation Therapy: Initial Characterization and Demonstration with CT Simulation Images”, SPIE Medical Imaging Conference Proceedings, 2017, Proceeding Volume 10136. Oral Presentation, doi:10.1117/12.2254063.
  • Steven Dolly, Mark Anastasio, Hua Li*, “Learning-based Stochastic Object Models for Use in Optimizing Imaging System”, SPIE Medical Imaging Conference Proceedings, 2017, Proceeding Volume 10132. Oral Presentation, doi:10.1117/12.2254055.
  • Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera, “Robust Cancer Treatment Outcome Prediction Dealing with Small-sized and Imbalanced Data from FED-PET Images”, 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’2016), Oct. 17-21, 2016, Athens, Greece, pp.61-69. Doi:10.1007/978-3-319-46723- 88
  • Jerome Lapuyade-Lahorgue, Su Ruan, Hua Li, Pierre Vera, “Tumor Segmentation by Fusion of MRI Images Using Copula Based Statistical Methods”, International Conference of Image Processing (ICIP’2016), Phoenix, Arizona, USA. Sept. 2016
  • Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera, “Dempster-Shafer Theory based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy”, 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’2015), Oct. 5-9, 2015, Munich, Germany, LNCS 9351, PP: 695-702.
  • Hua Li*, Lifeng Yu, Luis S. Guimaraes, Joe G. Fletcher, Cynthia H. McCollough, “Evaluation of dual-front active contour segmentation and metal shadow filling methods on metal artifact reduction in multi-slice helical CT”, SPIE Medical Imaging, Feb 13-18, 2010, Vol. 7622.
  • Hua Li*, Anthony Yezzi, Laurent Cohen, “3D Multi-branch Tubular Surface and Centerline Extraction With 4D Iterative Key Points”, 12th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’2009), Sept. 20-24, 2009, London, UK, LNCS 5762, pp:1042-1050.
  • Hua Li*, Lifeng. Yu, Xin. Liu, Cynthia. H. McCollough, “Metal Artifact Suppression from Reformatted Projections in Multi-Slice Helical CT Using Dual-Front Active Contours”, IEEE EMBS’2009, Sept. 2-6, 2009, Minneapolis, MN, USA. (Invited Paper)
  • Hua Li*, Wade L. Thorstad, Kenneth J. Biehl, Richard Laforest, Yi Su, Kooresh I. Shoghi, Eric D. Donnelly, Daniel A. Low, Wei Lu, “A Novel PET Head and Neck Tumor Delineation Approach based on Adaptive Region-Growing and Dual-front Active Contours”, International Conference on the Use of Computers in Radiation Therapy (ICCR’2007), June 4-7, 2007, Toronto, Canada.
  • Hua Li*, Anthony Yezzi, “Vessels as 4D Curves: Global Minimal 4D Paths to Extract 3D Tubular Surfaces,” 2006 Conference on Computer Vision and Pattern Recognition workshop (CVPRW’06), 2006, pp.82-82, doi: 10.1109/CVPRW.2006.210.
  • Hua Li*, Anthony Yezzi, “Local or Global Minima: Flexible Dual-Front Active Contours”, International Conference of Computer Vision (ICCV’2005) Workshop- “Computer Vision in Biomedical Imaging”, Oct., 2005, Beijing, China, LNCS 3765, pp:356-366. (Best Paper Award)
  • Hua Li*, Anthony Yezzi, Laurent Cohen, “Fast 3D Brain Segmentation Using Dual-Front Active Contours with Optional User-Interaction”, International Conference of Computer Vision (ICCV’2005) Workshop-“Computer Vision in Biomedical Imaging, Oct., 2005, Beijing, China, LNCS 3765, pp:335-345.

Selected Conference Abstracts:

  • Jian Wu, Chunfeng Lian, Su Ruan, Sasa Mutic, Mark Anastasio, Hiram Gay, Wade Thorstad, Xiaowei Wang, Hua Li*. “Selecting Predictive Geometric Biomarkers for Oropharyngeal Cancer Treatment Prediction by Use of Advanced Machine Learning Method”, AAPM Annual Meeting, 2018. (Winner of The Jack Krohmer Junior Investigator Competition)
  • Jan Wu, Su Ruan, Chunfeng Lian, Sasa Mutic, Mark Anastasio, Hua Li*, “Medical Image Annotation with a New Low-Rank Modeling-Based Multi-Label Active Learning Method”, AAPM Annual Meeting, 2018. (Oral Presentation)
  • Jian Wu, Nalini Daniel, Hilary Lashmett, Thomas Mazur, Michael Gach, Laura Ochoa, Imran Zoberi, Su Ruan, Mark Anastasio, Sasa Mutic, Maria Thomas, Hua Li*, “ Deep Boltzmann Machines-Driven Method for In-Treatment Heart Motion Tracking Using Cine MRI”, International Society for Magnetic Resonance in Medicine (ISMRM) 25th Annual Meeting, Hawaii, April 22-27, 2017. (Oral presentation, <10% acceptance rate)
  • Jian Wu, Thomas Mazur, H. Michael Gach, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Brian McClain, Chunfeng Lian, Su Ruan, Mark Anastasio, Sasa Mutic, Maria Thomas, Hua Li*, Deep Boltzmann Machines-Driven Level Set Method for Heart Motion Tracking Using Cine MRI, AAPM Annual Meeting, 2017. (Oral presentation in Science Council Session on “Big Data, Deep Learning, and AI in Imaging and Radiation Oncology”)
  • Tianyu Zhao, Nilesh Mistry, Andre Ritter, Baozhou Sun, Hua Li, Sasa Mutic, “Evaluation of the Use of Direct Electron Density CT Images in Radiation Therapy”, AAPM Annual Meeting, 2016.(Best in Physics)
  • Hsin-Chen Chen, Steven Dolly, James Victoria, Mark Anastasio, Su Ruan, Daniel A. Low, Harold Li, H. Omar Wooten, James Dempsey, Hiram Gay, Sasa Mutic, Wade Thorstad, Hua Li*, “An Integrated Model-Based Intrafractional Motion Tracking Approach With Dynamic MRI In Head And Neck Radiotherapy”, AAPM Annual Meeting, 2015. (Best in Physics)
  • Chunfeng Lian, Hua Li*, Thierry Denoeux, Hsin-Chen Chen, Clifford Robinson, Pierre Vera, Su Ruan, “Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging”, AAPM Annual Meeting, 2015. (A finalist for the John R. Cameron Young Investigator competition)
  • Hsin-Chen Chen, James Kavanaugh, Jun Tan, Steven Dolly, Hiram Gay, Wade Thorstad, Mark Anastasio, Michael Altman, Sasa Mutic, Hua Li*, “A Supervised Framework for Automatic Contour Assessment for Radiotherapy Planning of Head-Neck Cancer”, AAPM Annual Meeting, 2014. (Best in Physics)

*Denotes corresponding or senior authorship.