Abstract
Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates and leads to dilatation of the ventricles. Measuring ventricular volume quantitatively is an important step in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular dilatation and deformation. Ventricle volume as a global indicator, however, does not allow for the precise analysis of local ventricular changes. In this work, we propose a 3D+t spatial-temporal nonlinear registration approach, which is used to analyze the detailed local changes of the ventricles of preterm IVH neonates from 3D US images. In particular, a novel sequential convex/dual optimization is introduced to extract the optimal 3D+t spatial-temporal deformable registration. The experiments with five patients with 4 time-point images for each patient showed that the proposed registration approach accurately and efficiently recovered the longitudinal deformation of the ventricles from 3D US images. To the best of our knowledge, this paper reports the first study on the longitudinal analysis of the ventriclar system of pre-term newborn brains from 3D US images.
Chapter PDF
Similar content being viewed by others
References
Ashburner, J., Friston, K.J.: Unified segmentation. NeuroImage 26(3), 839–851 (2005)
Baust, M., Zikic, D., Navab, N.: Diffusion-based regularisation strategies for variational level set segmentation. In: BMVC, pp. 1–11 (2010)
Breeze, A.C., Alexander, P., Murdoch, E.M., Missfelder-Lobos, H.H., Hackett, G.A., Lees, C.C.: Obstetric and neonatal outcomes in severe fetal ventriculomegaly. Prenatal Diagnosis 27(2), 124–129 (2007)
Chen, Y., An, H., Zhu, H., Jewells, V., Armao, D., Shen, D., Gilmore, J.H., Lin, W.: Longitudinal regression analysis of spatial–temporal growth patterns of geometrical diffusion measures in early postnatal brain development with diffusion tensor imaging. NeuroImage 58(4), 993–1005 (2011)
Dai, Y., Shi, F., Wang, L., Wu, G., Shen, D.: ibeat: a toolbox for infant brain magnetic resonance image processing. Neuroinformatics 11(2), 211–225 (2013)
Dai, Y., Wang, Y., Wang, L., Wu, G., Shi, F., Shen, D., Initiative, A.D.N., et al.: abeat: A toolbox for consistent analysis of longitudinal adult brain mri. PloS One 8(4), e60344 (2013)
Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al.: Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3), 341–355 (2002)
Kishimoto, J., de Ribaupierre, S., Lee, D., Mehta, R., St Lawrence, K., Fenster, A.: 3D ultrasound system to investigate intraventricular hemorrhage in preterm neonates. Physics in Medicine and Biology 58(21), 7513 (2013)
Klebermass-Schrehof, K., Rona, Z., Waldhör, T., Czaba, C., Beke, A., Weninger, M., Olischar, M.: Can neurophysiological assessment improve timing of intervention in posthaemorrhagic ventricular dilatation? Archives of Disease in Childhood-Fetal and Neonatal Edition 98(4), F291–F297 (2013)
Qiu, W., Yuan, J., Kishimoto, J., McLeod, J., de Ribaupierre, S., Fenster, A.: User-guided segmentation of preterm neonate ventricular system from 3d ultrasound images using convex optimization. Ultrasound in Medicine & Biology 41(2), 542–556 (2015)
Qiu, W., Yuan, J., Ukwatta, E., Sun, Y., Rajchl, M., Fenster, A.: Dual optimization based prostate zonal segmentation in 3D MR images. Medical Image Analysis 18(4), 660–673 (2014)
Qiu, W., Yuan, J., Ukwatta, E., Sun, Y., Rajchl, M., Fenster, A.: Prostate segmentation: An efficient convex optimization approach with axial symmetry using 3D TRUS and MR images. IEEE Trans. Med. Imag. 33(4), 947–960 (2014)
Sun, Y., Yuan, J., Qiu, W., Rajchl, M., Romagnoli, C., Fenster, A.: Three-dimensional non-rigid mr-trus registration using dual optimization. IEEE Transactions on Medical Imaging 34(5), 1085–1094 (2015)
de Vries, L.S., Brouwer, A.J., Groenendaal, F.: Posthaemorrhagic ventricular dilatation: when should we intervene? Archives of Disease in Childhood-Fetal and Neonatal Edition 98(4), F284–F285 (2013)
Yuan, J., Bae, E., Tai, X.C.: A study on continuous max-flow and min-cut approaches. In: CVPR (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Qiu, W. et al. (2015). Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9351. Springer, Cham. https://doi.org/10.1007/978-3-319-24574-4_57
Download citation
DOI: https://doi.org/10.1007/978-3-319-24574-4_57
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24573-7
Online ISBN: 978-3-319-24574-4
eBook Packages: Computer ScienceComputer Science (R0)