Lung Fields Segmentation Algorithm in Chest Radiography

Accurate segmentation of lung fields in chest radiography is an essential part of computer-aided detection. We proposed a segmentation method by use of feature images, gray and shape cost, and modification method. The outline of lung fields in the training set was marked and aligned to create an initial outline. Then, dynamic program was employed to determine the optimal one in terms of the gray and shape cost in the six feature images. Finally, the lung outline was modified by Active Shape Model. The experimental results show that the average segmentation overlaps without and with feature images achieve 82.18% and 89.07%, respectively. After the modification of segmentation, the average overlap can reach 90.26%.