MRI ventilation analysis by merging parametric active contours

A novel technique that combines MR imaging of hyperpolarized helium gas and conventional MR imaging facilitates, high resolution imaging of lung functionality for the first time. We put forth a segmentation method for measuring the total lung air space and a classification approach to computing the functional air space. For segmentation, we introduce a parametric active contour that allows automated merging of multiple contours. The active contour technique uses gradient vector flow modified and strengthened by a boundary condition that inhibits contour crossover. The active contour approach is computationally inexpensive and is independent of initial contour placement. For classification of the functional lung air space in the helium images, a fuzzy c-means technique is applied. The classification results, in conjunction with the segmentation, allow the analysis of ventilation. The resultant biomedical image analysis tool can used in determining the efficacy of certain respiratory treatments