Key points are not available for this paper at this time.
In this paper, an algorithm for segmenting chest radiographs is presented where the left and right lungs are analysed separately. For each lung, a minimum rectangular frame is first determined, which completely encloses the object to be processed. The vertical edges of the minimum rectangular frame are determined by using the horizontal signature. The horizontal edges of the rectangular frame are determined by exploiting both the vertical signatures and the maximum vertical gradient sums. The image enclosed within the rectangular frame is called the subimage and its histogram is calculated. Segmentation into two classes is based upon grey level histogram thresholding, where the pixels less than a prefixed threshold are set to the background and those above to the foreground. The choice of threshold value is based upon a priori knowledge about the chest radiograph. Finally, a noise removal process is applied to smooth the boundaries: the top borders are refined by parabolas and the side borders by straight lines. Simulations are carried out on several chest radiographs and demonstrate the effectiveness of the proposed segmentation algorithm.
Cheng et al. (Tue,) studied this question.