Application of Diffusion Models for Image Reconstruction in Electrical Impedance Tomography

• Grant number: 24/13357-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2024
• End date: August 31, 2025
• Field of knowledge: Engineering - Biomedical Engineering - Medical Engineering
• Principal Investigator: Marcos de Sales Guerra Tsuzuki
• Grantee: Mateus Sudan Parducci
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Electrical Impedance Tomography (EIT) is a non-invasive imaging technique that stands out for not relying on harmful radiation and for the portability of its equipment, making it promising for medical applications such as lung imaging and brain activity monitoring. However, it faces challenges in image quality due to the ill-posed nature of the inverse problem. This research project aims to use Diffusion Models, an advanced deep learning technique, to enhance image reconstruction in EIT. The Diffusion Model will be trained on a simulated EIT dataset. We aim to develop a Diffusion Model adapted for EIT, create a comprehensive set of simulated data, train and validate the model, and publish the results.