Identity Recognition Based On Chest Radiography

Chest radiography is one of the most popular medical imaging diagnosis methods in clinical practice. Large amount of chest radiographs are produced in X-ray department every day. Mistakes in archiving these images will lead to serious consequence. In this paper identity recognition based on DICOM chest radiography is researched, which is helpful to reduce mis-archiving. For this purpose, preprocess, segmentation and identification of chest radiographies is discussed.Preprocess and segmentation are discussed in this paper. Firstly, many classical algorithms are reviewed. Combining With these algorithms, such as profiling, clustering, threshold segmentation, gradient edge detection, model matching, edge tracing, A new method is put forward to extract ROI of anatomical structure, segmentation of lung field, edges of ribs and clavicle. This integrated method produces wonderful results. Furthermore, new methods, such as pixel classification and active models, are adopted in this paper. Lung fields in 12 chest CR images are marked to train an AAM model and other 10 images are inputted for testing. We get a good segmentation result that only one mismatchs is identified.Identity recognition of chest radiography is a very new topic and little research experience can be found. In this paper, it is attempted to study patients'identity recognition through imitating how doctors do in clinic and how researchers do in fingerprint recognition and face recognition area. This problem...