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.
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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
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DOI: https://doi.org/10.1007/978-3-319-24574-4_57
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