Lei Du
Orcid: 0000-0002-6698-9814Affiliations:
- Northwestern Polytechnical University, School of Automation, Xi'an, China
According to our database1,
Lei Du
authored at least 46 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Identification of Genetic Risk Factors Based on Disease Progression Derived From Longitudinal Brain Imaging Phenotypes.
IEEE Trans. Medical Imaging, March, 2024
Modeling genotype-protein interaction and correlation for Alzheimer's disease: a multi-omics imaging genetics study.
Briefings Bioinform., January, 2024
Disease Progression Prediction Incorporating Genotype-Environment Interactions: A Longitudinal Neurodegenerative Disorder Study.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
A Bayesian Group Sparse Canonical Correlation Analysis Method for Brain Imaging Genomics.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
A Co-contrastive Learning Method to Fuse Multi-modal Phenotypes and Identify Genetic Risk Variations.
Proceedings of the 15th ACM International Conference on Bioinformatics, 2024
2023
inMTSCCA: An Integrated Multi-task Sparse Canonical Correlation Analysis for Multi-omic Brain Imaging Genetics.
Genom. Proteom. Bioinform., April, 2023
A multi-task SCCA method for brain imaging genetics and its application in neurodegenerative diseases.
Comput. Methods Programs Biomed., April, 2023
Adaptive structured sparse multiview canonical correlation analysis for multimodal brain imaging association identification.
Sci. China Inf. Sci., April, 2023
Identification of Disease-Sensitive Brain Imaging Phenotypes and Genetic Factors Using GWAS Summary Statistics.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Identifying Main and Epistasis Effects of Genetic Variations on Neuroimaging Phenotypes Using Effective Feature Interaction Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Identifying Disease-related Brain Imaging Quantitative Traits and Related Genetic Variations via A Bidirectional Association Learning Method.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
Identification of multimodal brain imaging association via a parameter decomposition based sparse multi-view canonical correlation analysis method.
BMC Bioinform., March, 2022
A Novel Two-Stage Multi-view Low-Rank Sparse Subspace Clustering Approach to Explore the Relationship Between Brain Function and Structure.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022
Bridging Natruralistic Stimuli, Eye Movement And Brain Activity Via Cca And Locality Preserving Projection.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
A Sparse Multi-task Contrastive and Discriminative Learning Method with Feature Selection for Brain Imaging Genetics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Identifying associations among genomic, proteomic and imaging biomarkers via adaptive sparse multi-view canonical correlation analysis.
Medical Image Anal., 2021
Corrigendum to Identifying associations among genomic, proteomic and imaging biomarkers via adaptive sparse multi-view canonical correlation analysis [Medical Image Analysis 70 (2021) 1-12/102003].
Medical Image Anal., 2021
Improved Multi-task SCCA for Brain Imaging Genetics via Joint Consideration of the Diagnosis, Parameter Decomposition and Network Constraints.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method.
IEEE Trans. Medical Imaging, 2020
Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach.
Medical Image Anal., 2020
Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification.
Bioinform., 2020
Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-task Regression.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
Mining High-order Multimodal Brain Image Associations via Sparse Tensor Canonical Correlation Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort.
Bioinform., 2019
Proceedings of the Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
2018
A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics.
Bioinform., 2018
Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
2017
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach.
Proceedings of the Information Processing in Medical Imaging, 2017
2016
BMC Syst. Biol., 2016
Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.
Bioinform., 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
2015
GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics.
Proceedings of the Brain Informatics and Health - 8th International Conference, 2015
2014
Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.
Bioinform., 2014
Accelerating Sparse Canonical Correlation Analysis for Large Brain Imaging Genetics Data.
Proceedings of the Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014