Automated Detection of Radiopaque Markers in Chest and Abdomen Radiography

: We aimed to develop a computerized method for the detection of radiopaque markers, such as R and L in chest and abdomen radiography by using the generalized Hough transform and the template matching. To develop the computerized method, we used 200 chest and abdomen images in our institution as training cases. First, two template images for R and L markers were created with the same exposure condition as a chest X-ray. Following various image processing, such as edge detection, thinning and Hough transformed, a look-up table that consisted of distance and direction pairs was built for the generalized Hough transform. All training images were preprocessed with median filter, edge detection, binarization, thinning, back ground removal and labeling. For candidates of markers that were detected as true positive or false positive, their vote and cross-correlation were calculated with the generalized Hough transform. To evaluate this proposed method, a validation test was performed with another database that consisted of 800 chest and abdomen images by use of Mahalanobis distance based on vote and cross-correlation in statistics. The precision of detecting the radiopaque markers for 800 test images was 99.9%. In addition, this method worked out well for some specific images in which markers were overlapped with a human body.