Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection

no code implementations • 7 Feb 2024 • Pramit Saha, Divyanshu Mishra, Felix Wagner, Konstantinos Kamnitsas, J. Alison Noble

Secondly, we introduce a modality imputation network (MIN) pre-trained in a multimodal client for modality translation in unimodal clients and investigate its potential towards mitigating the missing modality problem.

Federated Learning Imputation

Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos

no code implementations • 1 Nov 2023 • Divyanshu Mishra, He Zhao, Pramit Saha, Aris T. Papageorghiou, J. Alison Noble

To detect OOD samples in this context, the resulting model should generalise to the intra-anatomy variations while rejecting similar OOD samples.

Anatomy Out-of-Distribution Detection +1

Rethinking Semi-Supervised Federated Learning: How to co-train fully-labeled and fully-unlabeled client imaging data

no code implementations • 28 Oct 2023 • Pramit Saha, Divyanshu Mishra, J. Alison Noble

The most challenging, yet practical, setting of semi-supervised federated learning (SSFL) is where a few clients have fully labeled data whereas the other clients have fully unlabeled data.

Federated Learning Image Classification