ABSTRACT
A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can enhance interval changes on a chest radiograph by removal of most normal structures. However, subtraction artifacts, which tend to reduce its effectiveness in the detection of interval changes, were still included in the conventional method. In this study, we have developed a pixel matching technique to reduce artifacts in the temporal subtraction images. With this technique, the pixel value in a nonlinearly warped previous image is replaced by a pixel value within a kernel, which is closest to the pixel value on a current image. For evaluation of the proposed method, one hundred temporal subtraction images with a simulated nodule were used. When the kernel size of 3×3 was employed in the pixel matching technique, the misregistration artifacts decreased by 72%, and the contrast-to-noise ratio of the simulated lung nodules was increased by 5% in comparison with the conventional method. However, the area of the simulated nodule on the subtraction image decreased by 6%. Our results indicated that the pixel matching technique can enhance simulated nodules, with a substantial reduction of misregistration artifacts in comparison with conventional subtraction images. Therefore, we believe that the temporal subtraction method with the pixel matching technique would assist radiologists' diagnoses for detection of lung nodules in digital chest radiography.
