Automatic Segmentation of Lung Fields in Chest Radiographs

We present algorithms for the automatic delineation of lung fields in chest radiographs. We first develop a rule-based scheme that detects lung contours using a general framework for the detection of oriented edges and ridges. This algorithm is compared to several pixel classifiers using different combinations of features. We propose a hybrid system that combines both approaches. The performance of each system is compared with interobserver variability and results available from the literature. Our hybrid scheme turns out to be accurate and robust; the accuracy is 0.969 ± 0.00803, and above 94% for all 115 test images.