11 citations · 12 across the 5 of their papers we have counts for
5 papers
Pressure- and time-dependent alveolar recruitment/derecruitment in a spatially resolved patient-specific computational model for injured human lungs
Carolin M. Geitner, Lea J. Köglmeier, Inéz Frerichs +6
We present a novel computational model for the dynamics of alveolar recruitment/derecruitment (RD), which reproduces the underlying characteristics typically observed in injured lu…
An approach to study recruitment/derecruitment dynamics in a patient-specific computational model of an injured human lung
Carolin M. Geitner, Tobias Becher, Inéz Frerichs +3
We present a new approach for physics-based computational modeling of diseased human lungs. Our main object is the development of a model that takes the novel step of incorporating…
Classification of Electrical Impedance Tomography Data Using Machine Learning
Diogo Pessoa, Bruno Machado Rocha, Grigorios-Aris Cheimariotis +7
Patients suffering from pulmonary diseases typically exhibit pathological lung ventilation in terms of homogeneity. Electrical Impedance Tomography (EIT) is a non-invasive imaging…
Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models
Nils Strodthoff, Claas Strodthoff, Tobias Becher +2
Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows a continuous assessment of changes in regional bioimpedance of different organs. One of its most…
A parametric model for the changes in the complex valued conductivity of a lung during tidal breathing
Sven Nordebo, Mariana Dalarsson, Davood Khodadad +8
Classical homogenization theory based on the Hashin-Shtrikman coated ellipsoids is used to model the changes in the complex valued conductivity (or admittivity) of a lung during ti…