Electrical Impedance Tomography for Stroke Diagnosis Using Deep Neural Networks

• Grant number: 23/13729-0
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2024
• End date: 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.