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GLFNet: Global-Local (Frequency) Filter Networks for efficient Medical Image Segmentation

Tragakis, A., Liu, Q., Kaul, C., Kumar Roy, S., Dai, H., Deligianni, F. , Murray-Smith, R. and Faccio, D. (2024) GLFNet: Global-Local (Frequency) Filter Networks for efficient Medical Image Segmentation. In: 21st IEEE International Symposium on Biomedical Imaging, Athens, Greece, 27-30 May 2024, (Accepted for Publication)

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Abstract

No abstract available.

Item Type:Conference Proceedings
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Liu, Miss Qianying and Deligianni, Dr Fani and Tragakis, Athanasios and Dai, Dr Hang and Kaul, Dr Chaitanya and Faccio, Professor Daniele
Authors: Tragakis, A., Liu, Q., Kaul, C., Kumar Roy, S., Dai, H., Deligianni, F., Murray-Smith, R., and Faccio, D.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Physics and Astronomy

University Staff: Request a correction | Enlighten Editors: Update this record

Project Code
Award No
Project Name
Principal Investigator
Funder's Name
Funder Ref
Lead Dept
Privacy-Preserved Human Motion Analysis for Healthcare Applications
Fani Deligianni
EP/W01212X/1
Computing Science
QuantIC - The UK Quantum Technoogy Hub in Quantum Enhanced Imaging
Miles Padgett
EP/T00097X/1
P&S - Physics & Astronomy
Exploiting Closed-Loop Aspects in Computationally and Data Intensive Analytics
Roderick Murray-Smith
EP/R018634/1
Computing Science
Quantum-Inspired Imaging for Remote Monitoring of Health & Disease in Community Healthcare
Jonathan Cooper
EP/T021020/1
ENG - Biomedical Engineering

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