Lili He

According to our database, Lili He authored at least 16 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Hailong Li, Junqi Wang, Zhiyuan Li, Kim M. Cecil, Mekibib Altaye, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, 2024

RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-training.

Zhixiu Lu, Hailong Li, Lili He

CoRR, 2024

DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants.

Junqi Wang, Hailong Li, Kim M. Cecil, Mekibib Altaye, Nehal A. Parikh, Lili He

Comput. Methods Programs Biomed., 2024

Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment.

Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Mekibib Altaye, Kim M. Cecil, Nehal A. Parikh, Lili He

Artif. Intell. Medicine, 2024

2023

A novel collaborative self-supervised learning method for radiomic data.

Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, August, 2023

Dynamic weighted hypergraph convolutional network for brain functional connectome analysis.

Junqi Wang, Hailong Li, Gang Qu, Kim M. Cecil, Jonathan R. Dillman, Nehal A. Parikh, Lili He

Medical Image Anal., 2023

2022

A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants.

Zhiyuan Li, Hailong Li, Adebayo Braimah, Jonathan R. Dillman, Nehal A. Parikh, Lili He

NeuroImage, 2022

Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology.

Julia E. Kline, Jonathan Dudley, Venkata Sita Priyanka Illapani, Hailong Li, Beth Kline-Fath, Jean A. Tkach, Lili He, Weihong Yuan, Nehal A. Parikh

NeuroImage, 2022

A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy.

Xiangyu Zhao, Xueping Peng, Ke Niu, Hailong Li, Lili He, Feng Yang, Ting Wu, Duo Chen, Qiusi Zhang, Menglin Ouyang, Jiayang Guo, Yijie Pan

Frontiers Neuroinformatics, 2022

2019

Enhancing Diagnosis of Autism With Optimized Machine Learning Models and Personal Characteristic Data.

Milan N. Parikh, Hailong Li, Lili He

Frontiers Comput. Neurosci., 2019

2013

Automated detection of white matter signal abnormality using T2 relaxometry: Application to brain segmentation on term MRI in very preterm infants.

Lili He, Nehal A. Parikh

NeuroImage, 2013

2010

A Spatio-Temporal Deconvolution Method to Improve Perfusion CT Quantification.

Lili He, Burkay Orten, Synho Do, William Clement Karl, Avinish Kambadakone, Dushyant Sahani, Homer H. Pien

IEEE Trans. Medical Imaging, 2010

2009

A Nonlocal Maximum Likelihood Estimation Method for Rician Noise Reduction in MR Images.

Lili He, Ian R. Greenshields

IEEE Trans. Medical Imaging, 2009

Spatio-Temporal Deconvolution of Perfusion CT Data in Rectal Tumor Patients.

Lili He, Burkay Orten, Synho Do, W. Clem Karl, Avinish Kambadakone, Dushyant Sahani, Homer H. Pien

Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009

2008

An MRF spatial fuzzy clustering method for fMRI SPMs.

Lili He, Ian R. Greenshields

Biomed. Signal Process. Control., 2008

2005

Empirical Determination of Lower Bounds on RP Embedding.

Lili He, Ian R. Greenshields

Proceedings of the AI Technologies for Homeland Security, 2005