Defining the lung outline from a gamma camera transmission attenuation map

Segmentation of the lung outline from gamma camera transmission images of the thorax is useful in attenuation correction and quantitative image analysis. This paper describes and compares two threshold-based methods of segmentation. Simulated gamma camera transmission images of test objects were used to produce a knowledge base of the variation of threshold defining the lung outline with image resolution and chest wall thickness. Two segmentation techniques based on global (GT) and context-sensitive (CST) thresholds were developed and evaluated in simulated transmission images of realistic thoraces. The segmented lung volumes were compared to the true values used in the simulation. The mean distances between segmented and true lung surface were calculated. The techniques were also applied to three real human subject transmission images. The lung volumes were estimated and the segmentations were compared visually. The CST segmentation produced significantly superior segmentations than the GT technique in the simulated data. In human subjects, the GT technique underestimated volumes by 13% compared to the CST technique. It missed areas that clearly belonged to the lungs. In conclusion, both techniques segmented the lungs with reasonable accuracy and precision. The CST approach was superior, particularly in real human subject images.