Abstract #0875

On the prospects of deep learning for automated lung segmentation for functional lung MRI

Corin Willers¹, Grzegorz Bauman^2,3, Simon Andermatt³, Sylvia Nyilas⁴, Francesco Santini^2,3, Simon Pezold³, Philippe C. Cattin³, Philipp Latzin¹, Oliver Bieri^2,3, and Orso Pusterla²

¹Division of Pediatric Respiratory Medicine, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland, ²Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland, Basel, Switzerland, ³Department of Biomedical Engineering, University Basel, Basel, Switzerland, Basel, Switzerland, ⁴Department of Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

Deep learning algorithms have shown promise for precise organ segmentation. In this work, we investigate the prospects of deep learning for automated lung segmentation to assess impaired ventilation and perfusion measures using functional lung MRI.

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