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Abstract #1609

A Segmentation Pipeline for Measuring Pulmonary Ventilation Suitable for Clinical Workflows and Decision-making

Fumin Guo1, Khadija Sheikh1, Rachel Eddy1, Dante PI Capaldi1, David G McCormack2, Aaron Fenster1, and Grace Parraga1

1Robarts Research Institute, The University of Western Ontario, London, ON, Canada, 2Department of Medicine, The University of Western Ontario, London, ON, Canada

Clinical translation of hyperpolarized 129Xe MRI for large-scale and multi-centre applications requires image analysis tools that can provide clinically-acceptable measurements of pulmonary information. Here we proposed a pipeline that consists of 1H-129Xe registration, segmentation and ventilation defects generation for regional and quantitative evaluation of 129Xe ventilation. 1H-129Xe registration was performed using a state-of-art registration approach. 1H MRI segmentation was performed using primal-dual analysis methods and modern convex optimization techniques with incorporation of region information from 129Xe MRI. We applied the pipeline across a range of pulmonary abnormalities and this computationally efficient pipeline demonstrated high agreement with reference standard, suggesting its suitability for efficient clinical workflows.

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