Selection Strategies for Atlas-Based Mosaicing of Left Atrial 3-D Transesophageal Echocardiography Data

Abstract

Three-dimensional transesophageal echocardiography (TEE) provides real-time soft tissue information, but its use is hampered by its limited field of view. The mosaicing of multiple TEE views makes it possible to visualize a large structure, like the left atrium, in a single volume. To this end, an automatic registration method is required. Similarly to atlas-based segmentation approaches, atlas-based mosaicing (ABM) uses a full volume atlas set to moderate the onerous registration of the individual TEE views. The performance of ABM depends both on the quality of the involved registrations and on the selection of the optimal transformation from the candidate transformations that result from the various atlases. The study described here explored the performance of different selection strategies on multiview TEE data of the left atrium. We found that by incorporating two stages of transformation selection, using the image similarity and the conformity between the candidate transformations as selection criteria, the average registration error dropped below 3 mm with respect to manual registration of these data. Finally, we used this method for the automatic construction of a wide-view TEE volume of the left atrium.