Xiangyu Zhao

Orcid: 0000-0002-5269-3182

Affiliations:
  • Monash University, Melbourne, VIC, Australia
  • Shanghai Jiao Tong University, School of Biomedical Engineering, Shanghai, China (2021-2024)


According to our database1, Xiangyu Zhao authored at least 26 papers between 2021 and 2025.

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

Timeline

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Bibliography

2025
Exploring Multiconnectivity and Subdivision Functions of Brain Network via Heterogeneous Graph Network for Cognitive Disorder Identification.
IEEE Trans. Neural Networks Learn. Syst., July, 2025

AASeg: Artery-Aware Global-to-Local Framework for Aneurysm Segmentation in Head and Neck CTA Images.
IEEE Trans. Medical Imaging, March, 2025

REHRSeg: Unleashing the power of self-supervised super-resolution for resource-efficient 3D MRI segmentation.
Neurocomputing, 2025

Uni-COAL: A unified framework for cross-modality synthesis and super-resolution of MR images.
Expert Syst. Appl., 2025

Domain generalization for mammographic image analysis with contrastive learning.
Comput. Biol. Medicine, 2025

2024
RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation.
IEEE J. Biomed. Health Informatics, January, 2024

Distillation of multi-class cervical lesion cell detection via synthesis-aided pre-training and patch-level feature alignment.
Neural Networks, 2024

Spatial attention-based implicit neural representation for arbitrary reduction of MRI slice spacing.
Medical Image Anal., 2024

sTBI-GAN: An adversarial learning approach for data synthesis on traumatic brain segmentation.
Comput. Medical Imaging Graph., 2024

Exploiting Latent Classes for Medical Image Segmentation from Partially Labeled Datasets.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

MeLo: Low-Rank Adaptation is Better than Fine-Tuning for Medical Image Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage.
Brain Informatics, December, 2023

MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosis.
CoRR, 2023

Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images.
CoRR, 2023

AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation.
CoRR, 2023

CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning.
CoRR, 2023

Domain Generalization for Mammographic Image Analysis via Contrastive Learning.
CoRR, 2023

CAS-Net: Cross-View Aligned Segmentation by Graph Representation of Knees.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

One-Shot Traumatic Brain Segmentation with Adversarial Training and Uncertainty Rectification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Alias-Free Co-modulated Network for Cross-Modality Synthesis and Super-Resolution of MR Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Robust Cervical Abnormal Cell Detection via Distillation from Local-Scale Consistency Refinement.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Learnable Subdivision Graph Neural Network for Functional Brain Network Analysis and Interpretable Cognitive Disorder Diagnosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022
Prior Attention Network for Multi-Lesion Segmentation in Medical Images.
IEEE Trans. Medical Imaging, 2022

TBI-GAN: An Adversarial Learning Approach for Data Synthesis on Traumatic Brain Segmentation.
CoRR, 2022

2021
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism.
CoRR, 2021

D2A U-Net: Automatic segmentation of COVID-19 CT slices based on dual attention and hybrid dilated convolution.
Comput. Biol. Medicine, 2021


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