Federated Modality-specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation

arXiv:2403.11803v1 Announce Type: new
Abstract: Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to multimodal imaging applications. In practice, it is not uncommon that some FL participants only possess a subset of the complete imaging modalities, posing inter-modal heterogeneity as a challenge to effectively training a global model on all participants' data. In addition, each participant would expect to obtain a personalized model tailored for its local data characteristics from the …

abstract analysis anchors applications arxiv brain cs.cv federated learning image imaging medical modal multimodal personalized practice segmentation type