Abstract
Recently, a particle-filtering based framework was proposed to extract ‘global’ information from 2D ultrasound screening videos of the fetal heart, including the heart’s visibility, position, orientation, view classification and cardiac phase. In this paper, we consider how to augment that framework to describe the positions and visibility of important cardiac structures, including several valves and vessels, that are key to clinical diagnoses of congenital heart conditions in the developing heart. We propose a partitioned particle filtering architecture to address the problem of the high dimensionality of the resulting state space. The state space is partitioned into several sequential stages, which enables efficient use of a small number of particles. We present experimental results for tracking structures across several view planes in a real world clinical video dataset, and compare to expert annotations.
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Our C++ implementation is available at https://github.com/CPBridge/fetal_heart_analysis.
References
Baumgartner, C.F., Kamnitsas, K., Matthew, J., Fletcher, T.P., Smith, S., Koch, L.M., Kainz, B., Rueckert, D.: Real-time detection and localisation of fetal standard scan planes in 2D freehand ultrasound. arXiv abs/1612.05601 (2016). http://arxiv.org/abs/1612.05601
Bridge, C.P., Ioannou, C., Noble, J.A.: Automated annotation and quantitative description of ultrasound videos of the fetal heart. Med. Image Anal. 36, 147–161 (2017)
Chen, H., Dou, Q., Ni, D., Cheng, J.-Z., Qin, J., Li, S., Heng, P.-A.: Automatic fetal ultrasound standard plane detection using knowledge transferred recurrent neural networks. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 507–514. Springer, Cham (2015). doi:10.1007/978-3-319-24553-9_62
Liu, K., Skibbe, H., Schmidt, T., Blein, T., Palme, K., Brox, T., Ronneberger, O.: Rotation-invariant HOG descriptors using fourier analysis in polar and spherical coordinates. Int. J. Comput. Vis. 106(3), 342–364 (2014)
MacCormick, J., Isard, M.: Partitioned sampling, articulated objects, and interface-quality hand tracking. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 3–19. Springer, Heidelberg (2000). doi:10.1007/3-540-45053-X_1
Pézard, P., et al.: Influence of ultrasonographers’ training on prenatal diagnosis of congenital heart diseases: a 12-year population-based study. Prenat. Diagn. 28(11), 1016–1022 (2008)
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Bridge, C.P., Ioannou, C., Alison Noble, J. (2017). Localizing Cardiac Structures in Fetal Heart Ultrasound Video. In: Wang, Q., Shi, Y., Suk, HI., Suzuki, K. (eds) Machine Learning in Medical Imaging. MLMI 2017. Lecture Notes in Computer Science(), vol 10541. Springer, Cham. https://doi.org/10.1007/978-3-319-67389-9_29
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DOI: https://doi.org/10.1007/978-3-319-67389-9_29
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