15,446 research outputs found
Dilatation of Lateral Ventricles with Brain Volumes in Infants with 3D Transfontanelle US
Ultrasound (US) can be used to assess brain development in newborns, as MRI
is challenging due to immobilization issues, and may require sedation.
Dilatation of the lateral ventricles in the brain is a risk factor for poorer
neurodevelopment outcomes in infants. Hence, 3D US has the ability to assess
the volume of the lateral ventricles similar to clinically standard MRI, but
manual segmentation is time consuming. The objective of this study is to
develop an approach quantifying the ratio of lateral ventricular dilatation
with respect to total brain volume using 3D US, which can assess the severity
of macrocephaly. Automatic segmentation of the lateral ventricles is achieved
with a multi-atlas deformable registration approach using locally linear
correlation metrics for US-MRI fusion, followed by a refinement step using
deformable mesh models. Total brain volume is estimated using a 3D ellipsoid
modeling approach. Validation was performed on a cohort of 12 infants, ranging
from 2 to 8.5 months old, where 3D US and MRI were used to compare brain
volumes and segmented lateral ventricles. Automatically extracted volumes from
3D US show a high correlation and no statistically significant difference when
compared to ground truth measurements. Differences in volume ratios was 6.0 +/-
4.8% compared to MRI, while lateral ventricular segmentation yielded a mean
Dice coefficient of 70.8 +/- 3.6% and a mean absolute distance (MAD) of 0.88
+/- 0.2mm, demonstrating the clinical benefit of this tool in paediatric
ultrasound
Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates
The study of cerebral anatomy in developing neonates is of great importance for
the understanding of brain development during the early period of life. This
dissertation therefore focuses on three challenges in the modelling of cerebral
anatomy in neonates during brain development. The methods that have been
developed all use Magnetic Resonance Images (MRI) as source data.
To facilitate study of vascular development in the neonatal period, a set of image
analysis algorithms are developed to automatically extract and model cerebral
vessel trees. The whole process consists of cerebral vessel tracking from
automatically placed seed points, vessel tree generation, and vasculature
registration and matching. These algorithms have been tested on clinical Time-of-
Flight (TOF) MR angiographic datasets.
To facilitate study of the neonatal cortex a complete cerebral cortex segmentation
and reconstruction pipeline has been developed. Segmentation of the neonatal
cortex is not effectively done by existing algorithms designed for the adult brain
because the contrast between grey and white matter is reversed. This causes pixels
containing tissue mixtures to be incorrectly labelled by conventional methods. The
neonatal cortical segmentation method that has been developed is based on a novel
expectation-maximization (EM) method with explicit correction for mislabelled
partial volume voxels. Based on the resulting cortical segmentation, an implicit
surface evolution technique is adopted for the reconstruction of the cortex in
neonates. The performance of the method is investigated by performing a detailed
landmark study.
To facilitate study of cortical development, a cortical surface registration algorithm
for aligning the cortical surface is developed. The method first inflates extracted
cortical surfaces and then performs a non-rigid surface registration using free-form
deformations (FFDs) to remove residual alignment. Validation experiments using
data labelled by an expert observer demonstrate that the method can capture local
changes and follow the growth of specific sulcus
Recommended from our members
ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program
ToScA North America will address key areas of science,
including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast,
Educational Outreach, Data, Materials Science and Medical and Biological
Science.University of Texas High-Resolution X-ray CT Facility (UTCT);
Jackson School of Geosciences, The University of Texas at Austin;
Natural History Museum (London);
Royal Microscopical Society (Oxford, UK)Geological Science
Prenatal development of skull and brain in a mouse model of growth restriction
Patterns of covariation result from the over-lapping effect of several developmental processes. By perturbing certain specific developmental processes, ex-perimental studies contribute to a better understanding of their particular effects on the generation of phenotype. The aim of this work was to analyze the interactions among morphological traits of the skull and the brain during late prenatal life (18.5 days postconception) in mice exposed to maternal protein undernutrition. Images from the skull and brain were obtained through micro-computed tomography and 3D landmark coordinates were digitized in order to quantify shape and size of both structures with geometric morphometric techniques. The results highlight a systemic effect of protein restriction on the size of the skull and the brain, which were both significantly reduced in the under-nourished group compared to control group. Skull shape is partially explained by brain size, and patterns of shape variation were only partially coincident with previous re-ports for other ontogenetic stages, suggesting that allomet-ric trajectories across pre- and postnatal ages change their directions. Within the skull, neurocranial and facial shape traits covaried strongly, while subtle covariation was found between the shape of the skull and the brain. These find-ings are in line with former studies in mutant mice and reveal the importance of carrying out analyses of pheno-typic variation in a broad range of developmental stages. The present study contributes to the basic understanding of epigenetic relations among growing tissues and has di-rect implications for the field of paleoanthropology, where inferences about brain morphology are usually derived from skull remains.Los patrones de covariación entre rasgos fenotÃ-picos resultan de la acción de diversos procesos que se sola-pan durante el desarrollo. Los estudios experimentales cons-tituyen la aproximación más adecuada para evaluar el efecto de procesos especÃficos en la generación de tales patrones. El objetivo de este trabajo es analizar las interacciones entre rasgos morfológicos craneofaciales y cerebrales durante la vida prenatal tardÃa (18,5 dÃas posconcepción) en ratones ex-puestos a desnutrición proteica materna. Se obtuvieron imá-genes del cráneo y cerebro a partir de microtomografÃa com-putada y se digitalizaron landmarks en 3D para cuantificar la forma y tamaño con técnicas de morfometrÃa geométrica. Los resultados subrayan un efecto sistémico de la restricción proteica en el tamaño del cráneo y el cerebro. La forma del cráneo es parcialmente explicable por el tamaño cerebral y los patrones de variación en forma fueron sólo en parte coin-cidentes con los reportados antes para otras edades, lo cual sugiere que las trayectorias alométricas a lo largo de la vida pre- y posnatal cambian su dirección. Los rasgos de forma del neurocráneo y el esqueleto facial covariaron fuertemen-te, aunque se encontró una asociación débil entre la forma del cráneo y del cerebro. Estos resultados concuerdan con estudios previos en ratones mutantes y revelan la relevancia de analizar la variación fenotÃpica en distintas etapas. El pre-sente estudio contribuye al conocimiento básico de las inte-racciones epigenéticas entre tejidos en crecimiento y tiene implicancias en el campo paleoantropológico en el que las inferencias acerca de la morfologÃa cerebral son usualmen-te derivadas del análisis del cráneo.Fil: Barbeito Andrés, Jimena. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Gonzalez, Paula Natalia. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Hallgrimsson, Benedikt. University of Calgary; Canad
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