A neonatal atlas template for spatial normalization of whole-brain magnetic resonance images of newborns: Preliminary results

Kazemi, Kamran; Moghaddam, Hamid Abrishami; Grebe, Reinhard; Gondry-Jouet, Catherine; Wallois, Fabrice

doi:10.1016/j.neuroimage.2007.05.004

Cited by 88 publications

(101 citation statements)

References 16 publications

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“…The created phantom is composed of voxels measuring 1 mm × 1 mm × 1 mm and has been normalized to the stereotaxic space defined by the neonatal brain template 'GRAMFC T39-42' [18]. According to this normalization, the Anterior Commissure (AC) defines the origin of the phantom, the line connecting the Anterior and Posterior Commissures defines the y axis, and the ver- tical line that passes through the inter-hemispheric fissure and the AC point defines the z axis.…”

Section: Resultsmentioning

confidence: 99%

“…The coregistration method used is based on information theory as proposed by Collignon et al [7] and implemented in SPM5. The T1-weighted image is then normalized to the stereotaxic space as defined by the neonatal brain Template 'GRAMFC T39-42' [18]. Normalization was based on a technique developed by Ashburner and Friston [2] and implemented in SPM5.…”

Section: Stereotaxic Normalizationmentioning

confidence: 99%

“…This vector field was approximated by using a set of cosine basis functions for deformation. The cut-off frequency for the cosine basis functions in the nonlinear step was reduced to 10 mm, yielding 1430 basis functions (11 in x, 13 in y and 10 in z direction) compared to the default cut-off frequency of 25 mm used in SPM5 [18]. Finally, normalization parameters were applied to the T2 and PD-weighted images.…”

Section: Stereotaxic Normalizationmentioning

confidence: 99%

“…Accurate brain tissue quantification can be used to study early growth of various brain structures and morphologic changes in neurodevelopmental disorders such as epilepsy [27]. Current neonatal MR image analysis methods, such as segmentation and normalization [25,24,18,31], have been evaluated using local data sets that are not publicly available. Under these circumstances, it is difficult to reproduce experimental results and compare the performances of counterpart algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…BrainWeb) are not suitable for neonatal image analysis studies due to the marked anatomical differences between neonatal and adult cranium and cerebrum. The most obvious differences concern head and brain sizes, but much more intriguing are the differences in relative size and shape of substructures between neonates, children and adults [18]. Moreover, there are differences in neonatal brain MR image characteristics due to changes in brain tissue relaxation times.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Design and construction of a brain phantom to simulate neonatal MR images

Kazemi

Moghaddam

Grebe

et al. 2011

Computerized Medical Imaging and Graphics

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Section: Resultsmentioning

confidence: 99%

Section: Stereotaxic Normalizationmentioning

confidence: 99%

Section: Stereotaxic Normalizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design and construction of a brain phantom to simulate neonatal MR images

Kazemi

Moghaddam

Grebe

et al. 2011

Computerized Medical Imaging and Graphics

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Neurodevelopmental MRI brain templates for children from 2 weeks to 4 years of age

Sanchez

Richards

Almli

2011

Developmental Psychobiology

134

181

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Spatial normalization and segmentation of pediatric brain MRI data with adult templates may impose biases and limitations in pediatric neuroimaging work. To remedy this deficiency, we created a single database made up of a series of pediatric, age-specific MRI average brain templates. These average, age-specific templates were constructed from brain scans of individual children obtained from two sources: (1) the NIH MRI Study of Normal Brain Development and (2) MRIs from University of South Carolina’s McCausland Brain Imaging Center. Participants included young children enrolled at ages ranging from 8 days through 4.3 years of age. A total of 13 age group cohorts spanning the developmental progression from birth through 4.3 years of age were used to construct age-specific MRI brain templates (2 weeks, 3, 4.5, 6, 7.5, 9, 12, 15, 18 months, 2, 2.5, 3, 4 years). Widely-used processing programs (FSL, SPM, ANTS) extracted the brain and constructed average templates separately for 1.5T and 3T MRI volumes. The resulting age-specific, average templates showed clear changes in head and brain size across ages and between males and females, as well as changes in regional brain structural characteristics (e.g., myelin development). This average brain template database is available via our website (http://jerlab.psych.sc.edu/neurodevelopmentalmridatabase) for use by other researchers. Use of these age-specific, average pediatric brain templates by the research community will enhance our ability to gain a clearer understanding of the early postnatal development of the human brain in health and in disease.

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The SRI24 multichannel atlas of normal adult human brain structure

Rohlfing¹,

Zahr²,

Sullivan³

et al. 2009

Human Brain Mapping

380

299

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This paper describes the SRI24 atlas, a new standard reference system of normal human brain anatomy, that was created using template-free population registration of high-resolution magnetic resonance images acquired at 3T in a group of 24 normal control subjects. The atlas comprises anatomical channels (T1, T2, and proton density weighted), diffusion-related channels (fractional anisotropy, mean diffusivity, longitudinal diffusivity, mean diffusion-weighted image), tissue channels (CSF probability, gray matter probability, white matter probability, tissue labels), and two cortical parcellation maps. The SRI24 atlas enables multi-channel atlas-to-subject image registration. It is uniquely versatile in that it is equally suited for the two fundamentally different atlas applications: label propagation and spatial normalization. Label propagation, herein demonstrated using DTI fiber tracking, is enabled by the increased sharpness of the SRI24 atlas compared with other available atlases. Spatial normalization, herein demonstrated using data from a young-old group comparison study, is enabled by its unbiased average population shape property. For both propagation and normalization, we also report the results of quantitative comparisons with seven other published atlases: Colin27, MNI152, ICBM452 (warp5 and air12), and LPBA40 (SPM5, FLIRT, AIR). Our results suggest that the SRI24 atlas, although based on 3T MR data, allows equally accurate spatial normalization of data acquired at 1.5T as the comparison atlases, all of which are based on 1.5T data. Furthermore, the SRI24 atlas is as suitable for label propagation as the comparison atlases and detailed enough to allow delineation of anatomical structures for this purpose directly in the atlas.

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A neonatal atlas template for spatial normalization of whole-brain magnetic resonance images of newborns: Preliminary results

Cited by 88 publications

References 16 publications

Design and construction of a brain phantom to simulate neonatal MR images

Design and construction of a brain phantom to simulate neonatal MR images

Neurodevelopmental MRI brain templates for children from 2 weeks to 4 years of age

The SRI24 multichannel atlas of normal adult human brain structure

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