An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation

An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation

Abstract This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based framework emp...

Full description

Saved in:
Bibliographic Details
Main Authors: Sadia Sultana Chowa, Md Rahad Islam Bhuiyan, Mst. Sazia Tahosin, Asif Karim, Sidratul Montaha, Md. Mehedi Hassan, Mohd Asif Shah, Sami Azam
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Self-supervised learning
Contrastive learning
VGG-19
Attention-CNN
Federated learning
Privacy-preserving
Online Access:https://doi.org/10.1038/s41598-024-83972-6
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-024-83972-6

Similar Items