Automated Classification of Slice Positions for Chest X-ray CT Images: An Approach by a Genetic Algorithm

Abstract

We have developed an automated classification method for slice positions in chest X-ray CT images, which is based on the template matching by applying a genetic algorithm (GA), in order to increase the true positives and to reduce the false positives of mediastinal lymphnodes detected by our detection algorithm. Combining the GA method with a feature extraction one which we have already reported yielded 96% classification rate.