Temporal subtraction in chest radiography: mutual information as a measure of image quality.

摘要

PURPOSE: Temporal subtraction is used to detect the interval change in chest radiographs and aid radiologists in patient diagnosis. This method registers two temporally different images by geometrically warping the lung region, or "lung mask," of a previous radiographic image to align with the current image. The gray levels of every pixel in the current image are subtracted from the gray levels of the corresponding pixels in the warped previous image to form a temporal subtraction image. While temporal subtraction images effectively enhance areas of pathologic change, misregistration of the images can mislead radiologists by obscuring the interval change or by creating artifacts that mimic change. The purpose of this study was to investigate the utility of mutual information computed between two registered radiographic chest images as a metric for distinguishing between clinically acceptable and clinically unacceptable temporal subtraction images. METHODS: A radiologist subjectively rated the image quality of 138 temporal subtraction images using a 1 (poor) to 5 (excellent) scale. To objectively assess the registration accuracy depicted in the temporal subtraction images, which is the main factor that affects the quality of these images, mutual information was computed on the two constituent registered images prior to their subtraction to generate a temporal subtraction image. Mutual information measures the joint entropy of the current image and the warped previous image, yielding a higher value when the gray levels of spatially matched pixels in each image are consistent. Mutual information values were correlated with the radiologist's subjective ratings. To improve this correlation, mutual information was computed from a spatially limited lung mask, which was cropped from the bottom by 10%-60%. Additionally, the number of gray-level values used in the joint entropy histogram was varied. The ability of mutual information to predict the clinical acceptability of a temporal subtraction image was evaluated through receiver operating characteristic (ROC) analysis. RESULTS: The mean correlation coefficient obtained between mutual information computed on constituent images and the subjective rating of temporal subtraction image quality was 0.785. ROC analysis yielded an average Az value of 0.852 for the ability of mutual information to distinguish between temporal subtraction images of clinically acceptable and clinically unacceptable quality. CONCLUSIONS: The results of this study establish a relationship between mutual information and temporal subtraction registration accuracy and demonstrate the ability of mutual information to objectively indicate the presence of misregistration artifacts.