Abstract
Cardiac phase determination of 3D ultrasound (US) imaging has numerous applications including intra- and inter-modality registration of US volumes, and gating of live images. We have developed a novel and potentially clinically useful real-time three-dimensional (3D) cardiac motion gating technique that facilitates and supports 3D US-guided procedures. Our proposed real-time 3D-Masked-PCA technique uses the Principal Component Analysis (PCA) statistical method in combination with other image processing operations. Unlike many previously proposed gating techniques that are either retrospective and hence cannot be applied on live data, or can only gate respiratory motion, the technique is able to extract the phase of live 3D cardiac US data. It is also robust to varying image-content; thus it does not require specific structures to be visible in the US image. We demonstrate the application of the technique for the purposes of real-time 3D cardiac gating of trans-oesophageal US used in electrophysiology (EP) and trans-catheter aortic valve implantation (TAVI) procedures. The algorithm was validated using 2 EP and 8 TAVI clinical sequences (623 frames in total), from patients who underwent left atrial ablation and aortic valve replacement, respectively. The technique successfully located all of the 69 end-systolic and end-diastolic gating points in these sequences.
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Acknowledgements
We acknowledge financial support from the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London and King’s College Hospital NHS Foundation Trust. This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/L505328/1]. We also thank Guy’s and St Thomas’ Department of Cardiology for providing the data used.
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Panayiotou, M., Peressutti, D., King, A.P., Rhode, K.S., James Housden, R. (2017). Image-Based Real-Time Motion Gating of 3D Cardiac Ultrasound Images. In: Mansi, T., McLeod, K., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science(), vol 10124. Springer, Cham. https://doi.org/10.1007/978-3-319-52718-5_1
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