Classification of Electrical Impedance Tomography Data Using Machine Learning

no code implementations • 2 Aug 2021 • Diogo Pessoa, Bruno Machado Rocha, Grigorios-Aris Cheimariotis, Kostas Haris, Claas Strodthoff, Evangelos Kaimakamis, Nicos Maglaveras, Inéz Frerichs, Paulo de Carvalho, Rui Pedro Paiva

In this article, we present a new approach to promote the use of EIT data and the implementation of new clinical applications for differential diagnosis, with the development of several machine learning models to discriminate between EIT data from healthy and non-healthy subjects.

BIG-bench Machine Learning Classification +1

Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models

no code implementations • 19 Oct 2020 • Nils Strodthoff, Claas Strodthoff, Tobias Becher, Norbert Weiler, Inéz Frerichs

Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows a continuous assessment of changes in regional bioimpedance of different organs.