Modality Bank: Learn multi-modality images across data centers without sharing medical data

Author:

Chang Qi1,Qu Hui2,Yan Zhennan3,Gao Yunhe1,Baskaran Lohendran4,Metaxas Dimitris1

Affiliation:

1. Rutgers University,Department of Computer Science,Piscataway,New Jersey,USA

2. Adobe,CA,USA

3. SenseBrain Research,Princeton,New Jersey,USA

4. National Heart Centre Singapore, and Duke-National University Of Singapore,Department of Cardiovascular Medicine

Publisher

IEEE

Reference31 articles.

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3. Multimodal CT in Stroke Imaging: New Concepts

4. Comparison of CT, MRI and FDG-PET in response prediction of patients with locally advanced rectal cancer after multimodal preoperative therapy: Is there a benefit in using functional imaging?

5. Multimodality Screening of Hepatic Nodules in Patients With Congenital Heart Disease After Fontan Procedure: Role of Ultrasound, ARFI Elastography, CT, and MRI

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1. Anti-AsynDGAN: Black-box Membership Inference Attacks Against Medical Distributed Generation Models;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Multi-modality cardiac image computing: A survey;Medical Image Analysis;2023-08

3. Federated Learning on Multimodal Data: A Comprehensive Survey;Machine Intelligence Research;2023-06-01

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