Paper
10 March 2006 An ISO-surface folding analysis method applied to premature neonatal brain development
Claudia E. Rodriguez-Carranza, Francois Rousseau, Bistra Iordanova, Orit Glenn M.D., Daniel Vigneron, James Barkovich, Colin Studholme
Author Affiliations +
Abstract
In this paper we describe the application of folding measures to tracking in vivo cortical brain development in premature neonatal brain anatomy. The outer gray matter and the gray-white matter interface surfaces were extracted from semi-interactively segmented high-resolution T1 MRI data. Nine curvature- and geometric descriptor-based folding measures were applied to six premature infants, aged 28-37 weeks, using a direct voxelwise iso-surface representation. We have shown that using such an approach it is feasible to extract meaningful surfaces of adequate quality from typical clinically acquired neonatal MRI data. We have shown that most of the folding measures, including a new proposed measure, are sensitive to changes in age and therefore applicable in developing a model that tracks development in premature infants. For the first time gyrification measures have been computed on the gray-white matter interface and on cases whose age is representative of a period of intense brain development.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Claudia E. Rodriguez-Carranza, Francois Rousseau, Bistra Iordanova, Orit Glenn M.D., Daniel Vigneron, James Barkovich, and Colin Studholme "An ISO-surface folding analysis method applied to premature neonatal brain development", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441K (10 March 2006); https://doi.org/10.1117/12.652516
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Brain

Interfaces

Magnetic resonance imaging

In vivo imaging

Image segmentation

Convolution

Image processing

Back to Top