Kelei He

Orcid: 0000-0002-7264-9437

According to our database1, Kelei He authored at least 28 papers between 2019 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Structured prompt-guided knowledge injection for medical image segmentation.
Pattern Recognit., 2026

2025
Dual-scale enhanced and cross-generative consistency learning for semi-supervised medical image segmentation.
Pattern Recognit., 2025

Deep adaptive learning predicts and diagnoses CSVD-related cognitive decline using radiomics from T2-FLAIR: a multi-centre study.
npj Digit. Medicine, 2025

2024
One-step Structure Prediction and Screening for Protein-Ligand Complexes using Multi-Task Geometric Deep Learning.
CoRR, 2024

7T-Like T1-Weighted and TOF MRI Synthesis from 3T MRI with Multi-contrast Complementary Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

Hybrid Sharing for Multi-Label Image Classification.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Diving Segmentation Model into Pixels.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Multi-Scale Transformer Network With Edge-Aware Pre-Training for Cross-Modality MR Image Synthesis.
IEEE Trans. Medical Imaging, November, 2023

Cross-level Feature Aggregation Network for Polyp Segmentation.
Pattern Recognit., August, 2023

Dual-scale Enhanced and Cross-generative Consistency Learning for Semi-supervised Polyp Segmentation.
CoRR, 2023

2022
Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images.
Pattern Recognit., 2022

SLMT-Net: A Self-supervised Learning based Multi-scale Transformer Network for Cross-Modality MR Image Synthesis.
CoRR, 2022

Transformers in Medical Image Analysis: A Review.
CoRR, 2022

2021
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images.
IEEE Trans. Medical Imaging, 2021

Cascaded MultiTask 3-D Fully Convolutional Networks for Pancreas Segmentation.
IEEE Trans. Cybern., 2021

Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images.
Pattern Recognit., 2021

MetricUNet: Synergistic image- and voxel-level learning for precise prostate segmentation via online sampling.
Medical Image Anal., 2021

Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain Adaptation.
CoRR, 2021

2020
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation.
CoRR, 2020

TripletUNet: Multi-Task U-Net with Online Voxel-Wise Learning for Precise CT Prostate Segmentation.
CoRR, 2020

Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images.
CoRR, 2020

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19.
CoRR, 2020

Automatic Data Augmentation Via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks.
IEEE Trans. Medical Imaging, 2019

CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.
Medical Image Anal., 2019

MIDCN: A Multiple Instance Deep Convolutional Network for Image Classification.
Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

Hierarchical Representation For Ct Prostate Segmentation.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019


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