Scale Ratio ICP for 3D Registration of Coronary Venous Anatomy With Left Ventricular Epicardial Surface to Guide CRT Lead Placement
Computing Sciences and Computer Engineering
Multi-modality image fusion of 3D coronary venous anatomy from fluoroscopic venograms with left ventricular (LV) epicardial surface from single-photon emission computed tomography (SPECT) myocardial perfusion image (MPI) can provide both LV physiological information and venous anatomy for guiding CRT LV lead placement. However, it is difficult to match the time points between MPI and venograms because of heart beating and thus image acquisition of the different cardiac frames, which affects the accuracy of 3D fusion. To address this issue, this study introduces a scale ratio iterative closest point (S-ICP) algorithm to non-rigidly fuse images from two different modalities. Three steps, including the image reconstruction, image registration, and image overlay were implemented to complete the images fusion. First, the 3D fluoroscopic venous anatomy and SPECT LV epicardial surface were reconstructed. Second, a landmark-based registration method was performed as an initial registration of S-ICP. With the initialization, the S-ICP algorithm with a preset scale range completed a fine registration for SPECT-vein fusion. Third, the registered venous anatomy was overlaid onto the SPECT LV epicardial surface. Moreover, in order to validate the accuracy of the fusion, 3D CT venous anatomy was manually fused with the same SPECT LV epicardial surface, and then the distance-based mismatch errors between fluoroscopic veins and CT veins were evaluated. Five patients were enrolled. As a result, the overall mismatch error was 5.6±4.1mm, which is smaller than the pixel size of SPECT images (6.4mm).
Proceedings Volume 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
(2019). Scale Ratio ICP for 3D Registration of Coronary Venous Anatomy With Left Ventricular Epicardial Surface to Guide CRT Lead Placement. Proceedings Volume 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling.
Available at: https://aquila.usm.edu/fac_pubs/15985