45 citations · 87 across the 11 of their papers we have counts for
11 papers
Spatio-Temporal Representation Decoupling and Enhancement for Federated Instrument Segmentation in Surgical Videos
Zheng Fang, Xiaoming Qi, Chun-Mei Feng +3
Surgical instrument segmentation under Federated Learning (FL) is a promising direction, which enables multiple surgical sites to collaboratively train the model without centralizi…
Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Yuan Zhang, Xinfeng Zhang, Xiaoming Qi +4
Content generation modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for FCL
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…
DSCENet: Dynamic Screening and Clinical-Enhanced Multimodal Fusion for MPNs Subtype Classification
Yuan Zhang, Yaolei Qi, Xiaoming Qi +2
The precise subtype classification of myeloproliferative neoplasms (MPNs) based on multimodal information, which assists clinicians in diagnosis and long-term treatment plans, is o…
FedSODA: Federated Cross-assessment and Dynamic Aggregation for Histopathology Segmentation
Yuan Zhang, Yaolei Qi, Xiaoming Qi +4
Federated learning (FL) for histopathology image segmentation involving multiple medical sites plays a crucial role in advancing the field of accurate disease diagnosis and treatme…
Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentation
Yaolei Qi, Yuting He, Xiaoming Qi +2
Accurate segmentation of topological tubular structures, such as blood vessels and roads, is crucial in various fields, ensuring accuracy and efficiency in downstream tasks. Howeve…
NCAGC: A Neighborhood Contrast Framework for Attributed Graph Clustering
Tong Wang, Guanyu Yang, Qijia He +2
Attributed graph clustering is one of the most fundamental tasks among graph learning field, the goal of which is to group nodes with similar representations into the same cluster…
MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation
Zhangfu Dong, Yuting He, Xiaoming Qi +5
The nature of thick-slice scanning causes severe inter-slice discontinuities of 3D medical images, and the vanilla 2D/3D convolutional neural networks (CNNs) fail to represent spar…
EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
Yuting He, Rongjun Ge, Xiaoming Qi +6
3D complete renal structures(CRS) segmentation targets on segmenting the kidneys, tumors, renal arteries and veins in one inference. Once successful, it will provide preoperative p…
Deep Reinforcement Learning for Imbalanced Classification
Enlu Lin, Qiong Chen, Xiaoming Qi
Data in real-world application often exhibit skewed class distribution which poses an intense challenge for machine learning. Conventional classification algorithms are not effecti…