Name
Title | ||
|---|---|---|
Surface displacement based shape analysis of central brain structures in preterm-born children |
Abstract | ||
|---|---|---|
Many studies using T1 magnetic resonance imaging (MRI) data have found associations between changes in global metrics (e.g. volume) of brain structures and preterm birth. In this work, we use the surface displacement feature extracted from the deformations of the surface models of the third ventricle, fourth ventricle and brainstem to capture the variation in shape in these structures at 8 years of age that may be due to differences in the trajectory of brain development as a result of very preterm birth (24-32 weeks gestation). Understanding the spatial patterns of shape alterations in these structures in children who were born very preterm as compared to those who were born at full term may lead to better insights into mechanisms of differing brain development between these two groups. The T1 MRI data for the brain was acquired from children born full term (FT, n=14, 8 males) and preterm (PT, n=51, 22 males) at age 8-years. Accurate segmentation labels for these structures were obtained via a multi-template fusion based segmentation method. A high dimensional non-rigid registration algorithm was utilized to register the target segmentation labels to a set of segmentation labels defined on an average-template. The surface displacement data for the brainstem and the third ventricle were found to be significantly different (p < 0.05) between the PT and FT groups. Further, spatially localized clusters with inward and outward deformation were found to be associated with lower gestational age. The results from this study present a shape analysis method for pediatric MRI data and reveal shape changes that may be due to preterm birth. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1117/12.2216914 | Proceedings of SPIE |
Keywords | Field | DocType |
Shape analysis,brainstem,third ventricle,fourth ventricle,Pediatric MRI | Third ventricle,Computer vision,Very Preterm Birth,Anatomy,Segmentation,Image segmentation,Fourth ventricle,Artificial intelligence,Premature birth,Magnetic resonance imaging,Physics,Shape analysis (digital geometry) | Conference |
Volume | ISSN | Citations |
9788 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amanmeet Garg | 1 | 1 | 2.46 |
| Ruth E. Grunau | 2 | 61 | 4.98 |
| Karteek Popuri | 3 | 59 | 8.80 |
| Steven P. Miller | 4 | 2 | 2.41 |
| Bruce Bjornson | 5 | 7 | 1.61 |
| Kenneth J. Poskitt | 6 | 37 | 3.93 |
| Faisal Beg | 7 | 185 | 19.22 |