Influence of Normalization on the Analysis of Electroanatomical Maps with Manifold Harmonics
Electrical and anatomical maps (EAM) are built by cardiac navigation systems (CNS) and by Electrocardiographic Imaging systems for supporting arrhythmia ablation during electrophysiological procedures. Manifold Harmonics Analysis (MHA) has been proposed for analyzing the spectral properties of EAM of voltages and times in CNS by using a representation of the EAM supported by the anatomical mesh. MHA decomposes the EAM in a set of basis functions and coefficients which allow to conveniently reconstruct the EAM. In this work, we addressed the effect of normalization of the mesh spatial coordinates and the bioelectrical feature on the EAM decomposition for identifying regions with strong variation on the feature. For this purpose, a simulated EAM with three foci in a ventricular and in an atrial tachycardia was used. These foci were located at different distances amongst themselves, and different voltages were also considered. Our experiments show that it is possible to identify the foci origin by considering the first 3–5 projections only when normalization was considered, both for atrial and ventricular EAM. In this case, better quality in the EAM reconstruction was also obtained when using less basis functions. Hence, we conclude that normalization can help to identify regions with strong feature variation in the first stages of the EAM reconstruction.
KeywordsCardiac navigation system Electroanatomical maps Manifold harmonics Normalization Reconstruction Regionalization Focal tachycardia location Electrophysiological study
This work was supported in part by the Spanish Government with Research Projects TEC2013-48439-C4-1-R and TSI-020100-2010-0469.
- 1.Feld, G.K., Fleck, R.P., Chen, P.S., Boyce, K., Bahnson, T.D., Stein, J.B., Calisi, C.M., Ibarra, M.: Radiofrequency catheter ablation for the treatment of human type 1 atrial flutter. Identification of a critical zone in the reentrant circuit by endocardial mapping techniques. Circulation 86(4), 1233–1240 (1992)CrossRefGoogle Scholar
- 3.Sanromán-Junquera, M., Mora-Jiménez, I., Saiz, J., Tobón, C., García-Alberola, A., Rojo-Álvarez, J.L.: Quantitative spectral criteria for cardiac navigation sampling rate using manifold harmonics analysis. Comput. Cardiol. 39, 357–360 (2012)Google Scholar
- 4.Zhang, H., van Kaick, O., Dyer, R.: Spectral methods for mesh processing and analysis. In: Proceedings of the Eurographics State-of-the-art Report, pp. 1–22 (2007)Google Scholar
- 12.Garland, M., Heckbert, P.: Simplifying surfaces with color and textures using quadric error metrics. In: Proceedings of IEEE Visualization, pp. 263–270 (1998)Google Scholar