A Survey of Lung Segmentation Techniques

Lung diseases are the most common diseases which cause mortality worldwide. Different techniques are available for lung segmentation. Developing an effective computer-aided diagnosis (CAD) system for detecting lung diseases is of great clinical importance and can increase the patient’s chance of survival. In the present paper, segmentation techniques and the segmentation results after applying on the X-ray images are discussed. In segmentation, image is partitioned into a meaningful region and the result of image segmentation is a set of segments that collectively cover the entire image and all pixels in the segmented region which are similar with respect to some characteristic such as color, intensity, texture etc. Here some of the segmentation techniques such as edge detection, thresholding, and watershed transform etc. are applied on the chest X-ray image and the effectiveness of each technique is shown with the help of images and properties extracted. This paper overviews the current state-of-the-art techniques that have been developed to implement CAD processing steps. For each technique, various aspects of technical issues are described. In addition, the paper also addresses several challenges that researchers face in each implementation and also outlines the strengths and drawbacks of the existing approaches for lung CAD systems.. Keywords— Computer Aided Diagnosis (CAD), Segmentation, Thresholding, Transformation