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Electrical Impedance Tomography for Stroke Diagnosis Using Deep Neural Networks

Grant number: 23/13729-0
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): March 01, 2024
Effective date (End): January 31, 2028
Field of knowledge:Engineering - Electrical Engineering - Telecommunications
Principal Investigator:André Kazuo Takahata
Grantee:Yigermal Bassie Yassabie
Host Institution: Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas (CECS). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
Associated research grant:22/03243-0 - Interdisciplinary research of machine learning and artificial techniques for development of signal, image and natural language processing technologies, AP.PNGP.PI

Abstract

Several applications of interest today face the challenge of solving an inverse problem. An example of this type of problem in the medical field is image reconstruction from electrical impedance tomography (EIT), which has the potential to be a method for creating portable and continuous monitoring equipment. The objectives of this work will be the development of TIE signal processing techniques for brain image recovery and stroke diagnosis using deep learning techniques.

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