Airway segmentation and analysis for the study of mouse models of lung disease using micro-CT.

摘要: Animal models of lung disease are gaining importance in understanding the underlying mechanisms diseases such as emphysema and cancer. Micro-CT allows vivo imaging these models, thus permitting study progression or effect therapeutic drugs longitudinal studies. Automated analysis micro-CT images can be helpful to understand physiology diseased lungs, especially when combined with measurements respiratory system input impedance. In this work, we present a fast robust murine airway segmentation reconstruction algorithm. The algorithm is based on propagating marching wavefront that, it grows, divides tree into segments. We devised number specific rules guarantee that front propagates only inside airways avoid leaking parenchyma. was tested normal mice, mouse model chronic inflammation emphysema. A comparison manual segmentations two independent observers shows specificity sensitivity values our method comparable inter-observer variability, radius mainstem bronchi reveal significant differences between healthy mice. Combining automatically segmented parameters constant phase provides extra information how affects function.