Empirical Determination of Lower Bounds on RP Embedding. - Lili He 003; Ian R. Greenshields (AAAI Spring Symposium: AI Technologies for Homeland Security, 2005)

An MRF spatial fuzzy clustering method for fMRI SPMs. - Lili He 003; Ian R. Greenshields (Biomed. Signal Process. Control., 2008)

Spatio-Temporal Deconvolution of Perfusion CT Data in Rectal Tumor Patients. - Lili He 003; Burkay Orten; Synho Do; W. Clem Karl; Avinish Kambadakone; Dushyant Sahani; Homer H. Pien (ISBI, 2009)

A Nonlocal Maximum Likelihood Estimation Method for Rician Noise Reduction in MR Images. - Lili He 003; Ian R. Greenshields (IEEE Trans. Medical Imaging, 2009)

A Spatio-Temporal Deconvolution Method to Improve Perfusion CT Quantification. - Lili He 003; Burkay Orten; Synho Do; William Clement Karl; Avinish Kambadakone; Dushyant Sahani; Homer H. Pien (IEEE Trans. Medical Imaging, 2010)

Automated detection of white matter signal abnormality using T2 relaxometry: Application to brain segmentation on term MRI in very preterm infants. - Lili He 003; Nehal A. Parikh (NeuroImage, 2013)

Enhancing Diagnosis of Autism With Optimized Machine Learning Models and Personal Characteristic Data. - Milan N. Parikh; Hailong Li; Lili He 003 (Frontiers Comput. Neurosci., 2019)

A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy. - Xiangyu Zhao 004; Xueping Peng; Ke Niu 002; Hailong Li; Lili He 003; Feng Yang; Ting Wu; Duo Chen; Qiusi Zhang; Menglin Ouyang; Jiayang Guo; Yijie Pan (Frontiers Neuroinformatics, 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 003; Weihong Yuan; Nehal A. Parikh (NeuroImage, 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 011; Hailong Li; Adebayo Braimah; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2022)

Dynamic weighted hypergraph convolutional network for brain functional connectome analysis. - Junqi Wang 001; Hailong Li; Gang Qu 002; Kim M. Cecil; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (Medical Image Anal., 2023)

A novel collaborative self-supervised learning method for radiomic data. - Zhiyuan Li 011; Hailong Li; Anca L. Ralescu; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2023)

Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment. - Zhiyuan Li 011; Hailong Li; Anca L. Ralescu; Jonathan R. Dillman; Mekibib Altaye; Kim M. Cecil; Nehal A. Parikh; Lili He 003 (Artif. Intell. Medicine, 2024)

DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants. - Junqi Wang 001; Hailong Li; Kim M. Cecil; Mekibib Altaye; Nehal A. Parikh; Lili He 003 (Comput. Methods Programs Biomed., 2024)

RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-training. - Zhixiu Lu; Hailong Li; Lili He 003 (CoRR, 2024)

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome. - Hailong Li; Junqi Wang 001; Zhiyuan Li 011; Kim M. Cecil; Mekibib Altaye; Jonathan R. Dillman; Nehal A. Parikh; Lili He 003 (NeuroImage, 2024)