<title>Computerized Detection Of Lung Nodules In Digital Chest Radiographs</title>

Abstract

Detection of cancerous lung nodules in chest radiographs is one of the more important tasks performed by a radiologist. In addition, the miss rate associated with the radiographic detection of lung nodules is approximately 30%. A computerized scheme that alerts the radiologist to possible locations of lung nodules should allow this number of false-negative diagnoses to be reduced. We are developing a computer-aided nodule detection scheme based on a difference image approach. We attempt to eliminate the camouflaging background structure of the normal lung anatomy by creating, from a single-projection chest image, two images: one in which the signal-to-noise ratio (SNR) of the nodule is maximized and another in which that SNR is suppressed while the processed background remains essentially the same. Thus, the difference between these two processed images should consist of the nodule superimposed on a relatively uniform background in which the detection task may be simplified. This difference image approach is fundamentally different from conventional subtraction techniques (e.g., temporal or dual-energy subtraction) in that the two images which are subtracted arise from the same single-projection chest radiograph. Once the difference image is obtained, thresholding is performed along with tests for circularity, size and growth in order to extract the nodules. It should be noted that once an original chest image is input to the computer the nodule detection process is totally automated.