A fully automatic registration method for CARTO electro-anatomic map and CT surface

Catheter navigation guided by the registration of CARTO electro-anatomical map (EAM) and CT surface is a hotspot for atrial fibrillation (AF) treatment. However, research on the registration algorithm is just at its beginning. Physicians now extremely rely on Carto-Merge, a piece of software, to register EAM and CT surface during AF operations. Besides, only few studies have done on the algorithm. All these methods are semiautomatic or inaccurate for catheter navigation. Therefore, in this study, we proposed a principal axes based registration (PAR) method. Using normalized eigenvector, we first extract the principal axes of each image. Then, for each of the all kinds of axial correspondence, the average distance between the CT surface and the transformed EAM is estimated, and the one with the minimum distance is chosen as the final result. PAR is fully automatic. Furthermore, compared with Carto-Merge and the stochastic approach, an automatic EAM/CT registration algorithm, the experiments on both synthetic and real data show that PAR is much more accurate. At the same time, the speed of PAR is fast. In a word, our method can satisfy AF operations well.