Abstract #4355

Deep Learning Lung Segmentation in Paediatric Patients

Orso Pusterla^1,2, Simon Andermatt², Grzegorz Bauman^1,2, Sylvia Nyilas³, Philipp Madörin¹, Tanja Haas¹, Simon Pezold², Francesco Santini^1,2, Philipp Latzin³, Philippe Claude Cattin², and Oliver Bieri^1,2

¹Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland, ²Department of Biomedical Engineering, University of Basel, Basel, Switzerland, ³Division of Respiratory Medicine, Department of Pediatrics, Children's Hospital of Bern, Bern, Switzerland

Automatic lung segmentation of MR images is challenging; especially in the presence of pathologies. In this work, we tackle lung segmentation of 2D and 3D ultra-fast steady-state free precession MRI in cystic fibrosis patients by using deep learning based on a neural network of multi-dimensional gated recurrent units.

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