Digital image subtraction of temporally sequential chest images for detection of interval change

Abstract
An automated digital image subtraction technique for temporally sequential chest images has been developed in order to aid radiologists in the detection of interval changes. A number of small regions of interest (ROIs) are selected automatically in the lung areas of two temporally sequential chest images. A local matching, based on a cross-correlation method, is performed on each pair of corresponding ROIs in order to determine shift values for the coordinates of two images. A proper warping of x,y coordinates is obtained by fitting two-dimensional polynomials to the distributions of shift values. One of the images is warped and then subtracted from the other. Forty six pairs of chest images (42 with interval changes and 4 without interval change) were processed using this method. The subtraction images were able to enhance various important interval changes, such as differences in the size of tumor masses, changes in heart size, and changes in pulmonary infiltrates or pleural effusions. Approximately 70% of the pairs showed reasonably good registration.