Absolute alignment of breathing states using image similarity derivatives

摘要

The fusion of information in medical imaging relies on accurate registration of the image content coming often from different sources. One of the strongest influences on the movement of organs is the patient's respiration. It is known, that respiration status can be measured by comparing the projection images of the chest. Since the diaphragm compresses the soft tissue above, the level of similarity to a reference projection image in extremely inhaled or exhaled status gives an indication of the patient's respiration status. If the images to be registered are generated under different conditions the similarity with a common reference image is calculated on different scales and therefore cannot be compared directly. The proposed solution uses two reference images acquired in extremely inhaled and exhaled position. By comparing the images with two references and by combining the similarity results, changes in respiration depth between acquisitions can be detected. With normal breathing, the similarity to one of the reference images increases while the similarity to the other one decreases over time or vice versa. If the patient's respiration exceeds the respiration span of the reference images, the similarity to both reference images decreases. By using not only the similarity values but also their derivatives over time, changes in respiration depth therefore can be detected and the image fusion algorithm can act accordingly e.g. by removing images that exceed the valid respiration span.