Longitudinally guided level sets for consistent tissue segmentation of neonates
Article first published online: 3 DEC 2011
Copyright © 2011 Wiley Periodicals, Inc.
Human Brain Mapping
Volume 34, Issue 4, pages 956–972, April 2013
How to Cite
Wang, L., Shi, F., Yap, P.-T., Lin, W., Gilmore, J. H. and Shen, D. (2013), Longitudinally guided level sets for consistent tissue segmentation of neonates. Hum. Brain Mapp., 34: 956–972. doi: 10.1002/hbm.21486
- Issue published online: 11 MAR 2013
- Article first published online: 3 DEC 2011
- Manuscript Accepted: 12 SEP 2011
- Manuscript Revised: 11 SEP 2011
- Manuscript Received: 28 MAR 2011
- level sets;
- longitudinally guided segmentation;
- variational method
Quantification of brain development as well as disease-induced pathologies in neonates often requires precise delineation of white matter, grey matter and cerebrospinal fluid. Unlike adults, tissue segmentation in neonates is significantly more challenging due to the inherently lower tissue contrast. Most existing methods take a voxel-based approach and are limited to working with images from a single time-point, even though longitudinal scans are available. We take a different approach by taking advantage of the fact that the pattern of the major sulci and gyri are already present in the neonates and generally preserved but fine-tuned during brain development. That is, the segmentation of late-time-point image can be used to guide the segmentation of neonatal image. Accordingly, we propose a novel longitudinally guided level-sets method for consistent neonatal image segmentation by combining local intensity information, atlas spatial prior, cortical thickness constraint, and longitudinal information into a variational framework. The minimization of the proposed energy functional is strictly derived from a variational principle. Validation performed on both simulated and in vivo neonatal brain images shows promising results. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.