Paper
27 March 2009 Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images
Piotr A. Habas, Kio Kim, Dharshan Chandramohan, Francois Rousseau, Orit A. Glenn, Colin Studholme
Author Affiliations +
Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725917 (2009) https://doi.org/10.1117/12.812425
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Recent advances in MR and image analysis allow for reconstruction of high-resolution 3D images from clinical in utero scans of the human fetal brain. Automated segmentation of tissue types from MR images (MRI) is a key step in the quantitative analysis of brain development. Conventional atlas-based methods for adult brain segmentation are limited in their ability to accurately delineate complex structures of developing tissues from fetal MRI. In this paper, we formulate a novel geometric representation of the fetal brain aimed at capturing the laminar structure of developing anatomy. The proposed model uses a depth-based encoding of tissue occurrence within the fetal brain and provides an additional anatomical constraint in a form of a laminar prior that can be incorporated into conventional atlas-based EM segmentation. Validation experiments are performed using clinical in utero scans of 5 fetal subjects at gestational ages ranging from 20.5 to 22.5 weeks. Experimental results are evaluated against reference manual segmentations and quantified in terms of Dice similarity coefficient (DSC). The study demonstrates that the use of laminar depth-encoded tissue priors improves both the overall accuracy and precision of fetal brain segmentation. Particular refinement is observed in regions of the parietal and occipital lobes where the DSC index is improved from 0.81 to 0.82 for cortical grey matter, from 0.71 to 0.73 for the germinal matrix, and from 0.81 to 0.87 for white matter.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Piotr A. Habas, Kio Kim, Dharshan Chandramohan, Francois Rousseau, Orit A. Glenn, and Colin Studholme "Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725917 (27 March 2009); https://doi.org/10.1117/12.812425
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Cited by 12 scholarly publications.
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KEYWORDS
Brain

Image segmentation

Fetus

Magnetic resonance imaging

Tissues

Neuroimaging

Natural surfaces

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