System for EIT reconstruction based on Machine Learning techniques

• Autores: Martín Aller Dominguez, David Mera Pérez , José Manuel Cotos Yáñez , Ledicia Díaz Lago
• Localización: Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021): [Málaga, 22 al 24 de septiembre de 2021] / coord. por Rafael Capilla Sevilla , Maider Azanza Sese , Miguel Rodríguez Luaces , M. M. Roldán García , Dolores Burgueño Caballero, José Raúl Romero Salguero , José Antonio Parejo Maestre , José Francisco Chicano García , Marcela Genero , Óscar Díaz García , José González Enríquez , María Carmen Penades Gramage ; Silvia Mara Abrahao Gonzales (col.) , 2021
• Idioma: inglés
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• Resumen

  • Electrical Impedance Tomography (EIT) is a non-invasive technique that can be used to obtain information from inside bodies. To reconstruct internal body images using EIT, it is necessary to solve a mathematical ill-posed problem called inverse problem. We have developed a software called SageTomo that is able to reconstruct EIT images using Machine Learning techniques to solve the inverse problem. Furthermore, SageTomo allows users both to train and store Machine Learning models for EIT reconstruction, as well as to generate and store datasets for training these models.