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International Journal of Biomedical Imaging
Volume 2016, Article ID 7690391, 15 pages
http://dx.doi.org/10.1155/2016/7690391
Research Article

Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent

1Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, 91058 Erlangen, Germany
2Cardiac Arrhythmia Service, Hospital Barmherzige Brueder, 93049 Regensburg, Germany
3Erlangen Graduate School in Advanced Optical Technologies (SAOT), 91052 Erlangen, Germany
4Siemens Healthcare GmbH, 91301 Forchheim, Germany

Received 30 October 2015; Revised 7 February 2016; Accepted 7 February 2016

Academic Editor: Richard H. Bayford

Copyright © 2016 Matthias Hoffmann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient’s left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 6.3 mm and it dropped to 4.6 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 6.3 mm to 5.7 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods.