A region based active contour method for x-ray lung segmentation using prior shape and low level features

Authors:
P. Annangi;S. Thiruvenkadam;A. Raja;H. Xu;XiWen Sun;Ling Mao
Affiliations:
Imaging Technologies, GE Global Research;Imaging Technologies, GE Global Research;Imaging Technologies, GE Global Research;Imaging Technologies, GE Global Research;Shanghai Pulmonary Hospital, China;Shanghai Pulmonary Hospital, China
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

In this work, a level set energy for segmenting the lungs from digital Posterior-Anterior (PA) chest x-ray images is presented. The primary challenge in using active contours for lung segmentation is local minima due to shading effects and presence of strong edges due to the rib cage and clavicle. We have used the availability of good contrast at the lung boundaries to extract a multi-scale set of edge/corner feature points and drive our active contour model using these features. We found these features when supplemented with a simple region based data term and a shape term based on the average lung shape, able to handle the above local minima issues. The algorithm was tested on 1130 clinical images, giving promising results.