Abstract
Analysis of the X-ray image is one of the major issues in medical image processing. Trachea, bronchus, lung cancers are the seventh leading cause of death worldwide in 2008. The superimpositions of normal anatomical structures often cause interference, and many, 82%~95%, of the missed lung cancers were partly obscured by overlying bones such as ribs or a clavicle. We propose a segmentation method for ribs in chest radiographs to assist doctors in diagnosis. In this thesis, an unsupervised rib segmentation method is proposed based on existing mask of lung field. Some literatures deal with this problem based on a model fitting method. Instead of using a mathematical model as a template, we proposed another way achieving a good result. We utilize the designed rules of tracing from the border of mask of lung field to obtain a curve closer to the real edge. Because it is insufficient for using only one template to describe all ribs, we analyze all results of all templates in an image. After fine tuning, we keep routes with strong edge which satisfy all global features. The pairing procedure is performed on the edges. Finally, based on the paired edges as initial contour, active contour model is adopted to get the final result. The algorithm processes at different stages were characterized using edge and gray value, a coarse position is captured and gradually progressed to the final results. From the experimental results, the proposed algorithm can effectively segment the ribs in the chest radiographs.