A Robust Method for Estimating Regional Pulmonary Parameters in Presence of Noise

The reliability of parameters estimation in imaging-based regional functional measurements can be improved in the presence of noise by utilizing principal component analysis-based clustering without sacrificing spatial resolution compared to Cartesian binning. Results suggest that this approach has a great potential for robust grouping of pixels in hyperpolarized 3He MRI maps of lung oxygen tension.