Chao Li

Orcid: 0000-0002-0734-0011

Affiliations:
  • University of Cambridge, Department of Clinical Neuroscience, Department of Applied Mathematics and Theoretical Physics, UK
  • University of Dunde, School of Science and Engineering, School of Medicin, UK


According to our database1, Chao Li authored at least 21 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Multi-Modal Learning for Predicting the Genotype of Glioma.
IEEE Trans. Medical Imaging, November, 2023

Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks.
CoRR, 2023

Multi-task Learning of Histology and Molecular Markers for Classifying Diffuse Glioma.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

DisC-Diff: Disentangled Conditional Diffusion Model for Multi-contrast MRI Super-Resolution.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping.
Proceedings of the Computational Mathematics Modeling in Cancer Analysis, 2023

CoLa-Diff: Conditional Latent Diffusion Model for Multi-modal MRI Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Predicting Conversion of Mild Cognitive Impairment to Alzheimer's Disease by Modelling Healthy Ageing Trajectories.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Expectation-Maximization Regularised Deep Learning for Tumour Segmentation.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022
Multi-modal learning for predicting the genotype of glioma.
CoRR, 2022

Predicting conversion of mild cognitive impairment to Alzheimer's disease.
CoRR, 2022

Mutual Contrastive Learning to Disentangle Whole Slide Image Representations for Glioma Grading.
CoRR, 2022

Collaborative Learning of Images and Geometrics for Predicting Isocitrate Dehydrogenase Status of Glioma.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Radiological tumour classification across imaging modality and histology.
Nat. Mach. Intell., 2021

BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification.
CoRR, 2021

Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma.
CoRR, 2021

Quantifying Structural Connectivity in Brain Tumor Patients.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

BrainNetGAN: Data Augmentation of Brain Connectivity Using Generative Adversarial Network for Dementia Classification.
Proceedings of the Deep Generative Models, and Data Augmentation, Labelling, and Imperfections, 2021

Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural Networks.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for Glioblastoma.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2019
GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019


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