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Automation Through Deep-Learning To Quantify Ventilation Defects In Lungs From High-Resolution Isotropic Hyperpolarized 129xe Magnetic Resonance Imaging, Tuneesh Kaur Ranota

Electronic Thesis and Dissertation Repository

Obstructive lung diseases are characterized by heterogenous ventilation. Hyperpolarized ¹²⁹Xe gas lung magnetic resonance imaging (MRI) can examine lung ventilation heterogeneity by acquiring high-resolution isotropic images. The current gold standard of semi-automated (SA) segmentation can be used to quantify non-isotropic ¹²⁹Xe lung images to generate ventilation defect percent (VDP), however, this method is not suitable for analysis of isotropic voxel ¹²⁹Xe images due to the large number of slices. Therefore, we used a fully automated deep learning-based (DL) lung algorithm to calculate VDP from isotropic images. SNR, SA and DL-based VDP were calculated, showing a strong positive …