Zengqiang Yan

IEEE J. Biomed. Health Informatics, July, 2024

MFTrans: Modality-Masked Fusion Transformer for Incomplete Multi-Modality Brain Tumor Segmentation.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, January, 2024

APCAFlow: All-Pairs Cost Volume Aggregation for Optical Flow Estimation.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2024

UCTNet: Uncertainty-guided CNN-Transformer hybrid networks for medical image segmentation.

[BibT_eX]

[DOI]

Pattern Recognit., 2024

Boosting integral-based human pose estimation through implicit heatmap learning.

[BibT_eX]

[DOI]

Neural Networks, 2024

Non-parametric regularization for class imbalance federated medical image classification.

[BibT_eX]

[DOI]

Jeffry Wicaksana

CoRR, 2024

FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity.

[BibT_eX]

[DOI]

CoRR, 2024

SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts.

[BibT_eX]

[DOI]

CoRR, 2024

Weakly supervised learning for multi-class medical image segmentation via feature decomposition.

[BibT_eX]

[DOI]

Zhuo Kuang

Comput. Biol. Medicine, 2024

SAMPE: Auto-Prompting SAM for Generalizable Power Equipment Image Segmentation.

[BibT_eX]

[DOI]

IEEE Access, 2024

PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

FedMLP: Federated Multi-label Medical Image Classification Under Task Heterogeneity.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Revisiting Self-attention in Medical Transformers via Dependency Sparsification.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

DTMFormer: Dynamic Token Merging for Boosting Transformer-Based Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Cluster-Re-Supervision: Bridging the Gap Between Image-Level and Pixel-Wise Labels for Weakly Supervised Medical Image Segmentation.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, October, 2023

Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, August, 2023

MMA-Net: Multi-view mixed attention mechanism for facial action unit detection.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., August, 2023

BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, July, 2023

Hierarchical Associative Encoding and Decoding for Bottom-Up Human Pose Estimation.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., April, 2023

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2023

The Lighter the Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2023

SAMUS: Adapting Segment Anything Model for Clinically-Friendly and Generalizable Ultrasound Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2023

FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring.

[BibT_eX]

[DOI]

Jeffry Wicaksana

CoRR, 2023

FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Customized Federated Learning for Multi-Source Decentralized Medical Image Classification.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, 2022

Uncertainty-Aware Deep Learning With Cross-Task Supervision for PHE Segmentation on CT Images.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, 2022

Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation With Intra-Ventricular Hemorrhage.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, 2022

C2FTrans: Coarse-to-Fine Transformers for Medical Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2022

FedRare: Federated Learning with Intra- and Inter-Client Contrast for Effective Rare Disease Classification.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Variation-Aware Federated Learning With Multi-Source Decentralized Medical Image Data.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, 2021

Exploring intermediate representation for monocular vehicle pose estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Enabling a Single Deep Learning Model for Accurate Gland Instance Segmentation: A Shape-Aware Adversarial Learning Framework.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2020

2019

A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation.

[BibT_eX]

[DOI]

IEEE J. Biomed. Health Informatics, 2019

2018

A Skeletal Similarity Metric for Quality Evaluation of Retinal Vessel Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2018

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Biomed. Eng., 2018

Describing Upper-Body Motions Based on Labanotation for Learning-from-Observation Robots.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2018

A Deep Model with Shape-Preserving Loss for Gland Instance Segmentation.

[BibT_eX]

[DOI]

Kwang-Ting (Tim) Cheng

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Frequency Estimation of the Plenoptic Function Using the Autocorrelation Theorem.

[BibT_eX]

[DOI]

IEEE Trans. Computational Imaging, 2017

Texture edge-guided depth recovery for structured light-based depth sensor.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2017

2016

Describing upper body motions based on the Labanotation for learning-from-observation robots.

[BibT_eX]

[DOI]

CoRR, 2016

2015

Texture-free large-area depth recovery for planar surfaces.

[BibT_eX]

[DOI]

Zixiang Xiong

Proceedings of the 17th IEEE International Workshop on Multimedia Signal Processing, 2015

Large-area depth recovery for RGB-D camera.

[BibT_eX]

[DOI]