Abstract
The purpose of this study was to develop a novel computerized scheme to automatically select similar chest radiographs for image subtraction of patients who have no previous chest radiographs and to assist the radiologist's interpretation by presenting “similar subtraction images”. A large database of approximately 15,000 posteroanterior chest radiographs, which were diagnosed as normal, was used for searching similar images of different patients. First, in this scheme, two clinical parameters (age and sex) were used for selecting similar images. Next, 100 images of candidates in the database were selected according to similarity in height and the area of the lung field in the target image. We used quantitative measurement for searching similar images; namely, the correlation value of cheat region in the 100 images of the candidates. The similar subtraction images were obtained by subtracting the similar images selected from the target image. The performance of the proposed system was evaluated in comparison with 95 chest radiographs with a temporal subtraction image. The experimental results showed that the average of the correlation values in the temporal subtraction image and similar subtraction images were 0.9794 and 0.9574, respectively. Three radiologists subjectively evaluated various lung artifacts on the temporal subtraction image and similar subtraction images of 95 chest radiographs using a five-point rating scale (1: very poor, 2: poor, 3: adequate, 4: good, 5: excellent). Ratings higher than “adequate” were given for 70% of the similar subtraction images. This computerized scheme seems useful for the automatic selection of similar images for similar-image subtraction of chest radiographs and has potential use for assisting interpretations by radiologists.
