Fusing shape information in lung segmentation in chest radiographs

Authors:
Amer Dawoud
Affiliations:
School of Computing, University of Southern Mississippi, Hattiesburg, MS
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Year:
2010

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Abstract

This paper presents an algorithm for the segmentation of lung fields by fusing shape information priors into intensity-based thresholding in an iterative framework. The main contribution is to maximize information utilization by effectively combining intensity information with shape priors. Experimental results performed on publicly available database demonstrate the effectiveness of the algorithm in comparison with other algorithms.