2020 年 38 巻 5 号 p. 236-247
We previously proposed a pulmonary nodule clarification method for chest radiographs that controlled for the pulmonary vessels that were frequently extracted as false positives. In addition, further true pulmonary nodules were detected by applying a wavelet analysis and an error diffusion method to control for density alterations caused by clavicles, ribs, and peripheral pulmonary vessel shadows (background noise). However, this method was insufficient for extracting pulmonary nodules at the level of the pulmonary hilum. We herein report a new method for detecting such pulmonary nodules by applying cellular automata and adaptive rank filtering to the binary image produced using the error diffusion method. Two radiologists compared the new images obtained by the proposed technique with the background noise-suppressed pulmonary nodule-clarified images regarding suppression of the background noise and visibility (degree of emphasis) of the pulmonary nodules. This evaluation used 117 images with pulmonary nodules from the Japan Society of Radiological Technology database, excluding “extremely subtle” and “obvious” pulmonary nodules. While the pulmonary nodules at the level of the pulmonary hilum were enhanced, the background noise using the proposed method was not higher than that in our previous method in 76.1% of cases. The visibility of the pulmonary nodules was improved in 12.8% of cases. The proposed method for clarifying pulmonary nodules is expected to improve the detection of lung cancer nodules.
