4 citations · 4 across the 2 of their papers we have counts for
4 papers
Federated Modality-specific Encoders and Partially Personalized Fusion Decoder for Multimodal Brain Tumor Segmentation
Hong Liu, Dong Wei, Qian Dai +3
Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to multimodal imaging applications.…
Structure Observation Driven Image-Text Contrastive Learning for Computed Tomography Report Generation
Hong Liu, Dong Wei, Qiong Peng +4
Computed Tomography Report Generation (CTRG) aims to automate the clinical radiology reporting process, thereby reducing the workload of report writing and facilitating patient car…
FedSemiDG: Domain Generalized Federated Semi-supervised Medical Image Segmentation
Zhipeng Deng, Zhe Xu, Tsuyoshi Isshiki +1
Medical image segmentation is challenging due to the diversity of medical images and the lack of labeled data, which motivates recent developments in federated semi-supervised lear…
MoME: Mixture of Multimodal Experts for Cancer Survival Prediction
Conghao Xiong, Hao Chen, Hao Zheng +4
Survival analysis, as a challenging task, requires integrating Whole Slide Images (WSIs) and genomic data for comprehensive decision-making. There are two main challenges in this t…