Unsupervised Clustering Methods for Lung Perfusion Data Segmentation in Electrical Impedance Tomography
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49404-8_17
Reference12 articles.
1. Frerichs, I., Amato, M.B.P., van Kaam, A.H., et al.: Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the translational EIT development study group. Thorax 72, 83–93 (2016)
2. Perier, F., Tuffet, S., Maraffi, T., et al.: Effect of positive end-expiratory pressure and proning on ventilation and perfusion in COVID-19 acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 202(12), 1713–1717 (2020). PMID: 33075235
3. Perier, F., Tuffet, S., Maraffi, T., et al.: Electrical impedance tomography to titrate positive end-expiratory pressure in COVID-19 acute respiratory distress syndrome. Crit. Care 24(1), 678 (2020)
4. Leonhardt, S., Pikkemaat, R., Stenqvist, O., et al.: Electrical impedance tomography for hemodynamic monitoring. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 122–125. IEEE (2012)
5. Roldán, R., Rodriguez, S., Barriga, F., et al.: Sequential lateral positioning as a new lung recruitment maneuver: an exploratory study in early mechanically ventilated COVID-19 ARDS patients. Ann. Intensive Care 12(1), 13 (2022)
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