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Scale ratio ICP for 3D registration of coronary venous anatomy with left ventricular epicardial surface to guide CRT lead placement
Author(s): Haipeng Tang; Robert Bober; Chaoyang Zhang; Zhuo He; Jiangang Zou; Weihua Zhou
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Paper Abstract

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).

Paper Details

Date Published: 8 March 2019
PDF: 11 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 1095123 (8 March 2019); doi: 10.1117/12.2512775
Show Author Affiliations
Haipeng Tang, The Univ. of Southern Mississippi (United States)
Robert Bober, Ochsner Medical Ctr. (United States)
Chaoyang Zhang, The Univ. of Southern Mississippi (United States)
Zhuo He, The Univ. of Southern Mississippi (United States)
Jiangang Zou, First Affiliated Hospital of Nanjing Medical Univ. (China)
Weihua Zhou, The Univ. of Southern Mississippi (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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