Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
504140 | Computerized Medical Imaging and Graphics | 2012 | 12 Pages |
Abstract
Automatic and accurate lung field segmentation is an essential step for developing an automated computer-aided diagnosis system for chest radiographs. Although active shape model (ASM) has been useful in many medical imaging applications, lung field segmentation remains a challenge due to the superimposed anatomical structures. We propose an automatic lung field segmentation technique to address the inadequacy of ASM in lung field extraction. Experimental results using both normal and abnormal chest radiographs show that the proposed technique provides better performance and can achieve 3–6% improvement on accuracy, sensitivity and specificity compared to traditional ASM techniques.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Tao Xu, Mrinal Mandal, Richard Long, Irene Cheng, Anup Basu,