Hongming Li, Ph.D.
Research Associate
Artificial Intelligence in Biomedical Imaging Lab (AIBIL)
Center for Biomedical Image Computing & Analytics (CBICA)
Department of Radiology
Perelman School of Medicine
University of Pennsylvania
Richards Labs, Suite 700D
3700 Hamilton Walk
Philadelphia, PA 19104
Educational Qualifications
Ph.D. in Medical image analysis – Institute of Automation, Chinese Academy of Sciences (Beijing, China)
B.Sc. in Automation – Shandong University (Jinan, China)
Research Summary
My research interest focuses on the development of computational algorithms for medical image processing and their application in studies of brain images and cancer images
Publications
Journals
- Hongming Li, Yong Fan, "Interpretable, highly accurate brain decoding of subtly distinct brain states from functional MRI using intrinsic functional networks and long short-term memory recurrent neural networks", NeuroImage, 2019
- Hongming Li, Mohamad Habes, David A Wolk, Yong Fan, "A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data", Alzheimer's & Dementia, 2019
- Hongming Li, Maya Galperin-Aizenberg, Daniel Pryma, Charles B Simone II, Yong Fan, "Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy", Radiotherapy and Oncology, 2018, 129(2): 218-226
- Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Eric Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, Robert K Doot, Michel Bilello, Yong Fan, Russell T Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos, "Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome", Journal of Medical Imaging, 2018, 5(1): 011018
- Hongming Li, Theodore D. Satterhwaite, Yong Fan, "Large-scale sparse functional networks from resting state fMRI", NeuroImage, 156 (2017) 1-13
- Yinyan Wang, Xing Fan, Hongming Li, Zhiguo Lin, Hongbo Bao, Shaowu Li, Lei Wang, Tianzi Jiang, Yong Fan, Tao Jiang, "Tumor border sharpness correlates with HLA-G expression in low-grade Gliomas", Journal of Neuroimmunology, 282 (2015) 1-6
- Yinyan Wang, Kai Wang, Hongming Li, Jiangfei Wang, Lei Wang, Jianping Dai, Tao Jiang, Jun Ma, "Identifying the association of contrast enhancement with vascular endothelia growth factor expression in anaplastic gliomas: a volumetric magnetic resonance imaging analysis", PLoS ONE, 2015,10(3): e0121380
- Liping Fu, Hongming Li, Hui Wang, Baixuan Xu, Yong Fan, Jiahe Tian, "SUVmax/THKmax as a biomarker for distinguishing advanced gastric carcinoma from primary gastric lymphoma", PLoS ONE, 2012, 7(12): e50914
Conferences
- Hongming Li, Yong Fan, "Early prediction of Alzheimer's disease dementia based on baseline hippocampal MRI and 1-year follow-up cognitive measures using deep recurrent neural networks", IEEE International Symposium on Biomedical Imaging (ISBI), 2019
- Hongming Li, Pamela Boimel, James Janopaul-Naylor, Haoyu Zhong, Ying Xiao, Edgar Ben-Josef, Yong Fan, "Deep convolutional neural networks for imaging data based survival analysis of rectal cancer", IEEE International Symposium on Biomedical Imaging (ISBI), 2019
- Hangfan Liu, Hongming Li, Pamela Boimel, James Janopaul-Naylor, Haoyu Zhong, Ying Xiao, Edgar Ben-Josef, Yong Fan, "Collaborative clustering of subjects and radiomic features for predicting clinical outcomes of rectal cancer patients", IEEE International Symposium on Biomedical Imaging (ISBI), 2019
- Shi Yin, Zhengqiang Zhang, Hongming Li, Qinmu Peng, Xinge You, Susan L. Furth, Gregory E. Tasian, Yong Fan, "Fully-automatic segmentation of kidneys in clinical ultrasound images using a boundary distance regression network", IEEE International Symposium on Biomedical Imaging (ISBI), 2019
- Hongming Li, Xiaofeng Zhu, Yong Fan, "Identification of multi-scale hierarchical brain functional networks using deep matrix factorization", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
- Hongming Li, Yong Fan, "Identification of temporal transition of functional states using recurrent neural networks from functional MRI", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
- Hongming Li, Yong Fan, "Brain decoding from functional MRI using long short-term memory recurrent neural networks", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018
- Hongming Li, Yong Fan, "Non-rigid image registration using self-supervised fully convolutional networks without training data", IEEE International Symposium on Biomedical Imaging (ISBI), 2018
- Hongming Li, Theodore D. Satterhwaite, Yong Fan, "Brain age prediction based on resting-state functional connectivity patterns using convolutional neural networks", IEEE International Symposium on Biomedical Imaging (ISBI), 2018
- Xiaofeng Zhu, Hongming Li, Yong Fan, "Parameter-free centralized multi-task learning for characterizing developmental sex differences in resting state functional connectivity", AAAI Conferences on Artificial Intelligence (AAAI), 2018
- Hongming Li, Yong Fan, "Individualized brain parcellation with integrated functional and morphological information", IEEE International Symposium on Biomedical Imaging (ISBI), 2016
- Hongming Li, Ted Satterthwaite, Yong Fan, "Identification of subject-specific brain functional networks using a collaborative sparse nonnegative matrix decomposition method", IEEE International Symposium on Biomedical Imaging (ISBI), 2016
- Hongming Li, Yong Fan, "Hierarchical organization of the functional brain identified using floating aggregation of functional signals", IEEE International Symposium on Biomedical Imaging (ISBI), 2014
- Hongming Li, Yong Fan, "Spatial alignment of human cortex by matching hierarchical patterns of functional connectivity", IEEE International Symposium on Biomedical Imaging (ISBI), 2014
- Zhenyu Tang, Di Jiang, Hongming Li, Yong Fan, "Matching functional connectivity patterns for spatial correspondence detection in fmri registration", Medical Imaging and Augmented Reality (MIAR), in conjunction with MICCAI, 2013
- Hongming Li, Yong Fan, "Functional brain atlas construction for brain network analysis", SPIE Medical Imaging, 2013
- Hongming Li, Yong Fan, "Label propagation with robust initialization for brain tumor segmentation", IEEE International Symposium on Biomedical Imaging (ISBI), 2012
- Yuhui Du, Hongming Li, Yong Fan, "Identification of subject specific and functional consistent rois using semi-supervised learning", SPIE Medical Imaging, 2012
- Hongming Li, Ming Song, Yong Fan, "Segmentation of brain tumors in multi-parametric mr images via robust statistic information propagation", Asian Conference on Computer Vision (ACCV), 2010