| Records |
| Author |
Spalart, P.R. |
| Title |
Young-Persons Guide to Detached-Eddy Simulation Grids |
Type |
Journal Article |
| Year |
2001 |
Publication |
Nasa |
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211032 |
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no |
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refbase @ user @ PSpalart2001a |
Serial |
15131 |
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| Author |
Spalart, P.R. |
| Title |
Young-Persons Guide to Detached-Eddy Simulation Grids |
Type |
Journal Article |
| Year |
2001 |
Publication |
Nasa |
Abbreviated Journal |
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| Volume |
211032 |
Issue |
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Pages |
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no |
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refbase @ user @ PSpalart2001a |
Serial |
15300 |
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| Author |
salum |
| Title |
information |
Type |
Journal Article |
| Year |
19888 |
Publication |
tanzania |
Abbreviated Journal |
nil |
| Volume |
2673773 |
Issue |
2/5/1968 |
Pages |
2 |
| Keywords |
love is good |
| Abstract |
love is good |
| Address |
dar es salaam |
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sami |
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sami |
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no |
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refbase @ user @ |
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53986 |
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| Author |
Reese, B.E.; Barnett, R.E.; Alaoui-Ismaili, M.; Habibi, E.; Mann, C.J. |
| Title |
Quantitative Analysis of Living Cells by Digital Holographic Microscopy |
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Journal Article |
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Biomedical Engineering |
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| Volume |
37831 |
Issue |
6 |
Pages |
8-11 |
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no |
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refbase @ admin @ Reese |
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5587 |
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| Author |
Cherel, M.; Budin, F.; Prastawa, M.; Gerig, G.; Lee, K.; Buss, C.; Lyall, A.; Consing, K.Z.; Styner, M. |
| Title |
Automatic Tissue Segmentation of Neonate Brain MR Images with Subject-specific Atlases |
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Journal Article |
| Year |
2015 |
Publication |
Proceedings of SPIE--the International Society for Optical Engineering |
Abbreviated Journal |
Proc SPIE Int Soc Opt Eng |
| Volume |
9413 |
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| Keywords |
Mri; atlas; automatic; neonate; population; segmentation; subject-specific; tissue |
| Abstract |
Automatic tissue segmentation of the neonate brain using Magnetic Resonance Images (MRI) is extremely important to study brain development and perform early diagnostics but is challenging due to high variability and inhomogeneity in contrast throughout the image due to incomplete myelination of the white matter tracts. For these reasons, current methods often totally fail or give unsatisfying results. Furthermore, most of the subcortical midbrain structures are misclassified due to a lack of contrast in these regions. We have developed a novel method that creates a probabilistic subject-specific atlas based on a population atlas currently containing a number of manually segmented cases. The generated subject-specific atlas is sharp and adapted to the subject that is being processed. We then segment brain tissue classes using the newly created atlas with a single-atlas expectation maximization based method. Our proposed method leads to a much lower failure rate in our experiments. The overall segmentation results are considerably improved when compared to using a non-subject-specific, population average atlas. Additionally, we have incorporated diffusion information obtained from Diffusion Tensor Images (DTI) to improve the detection of white matter that is not visible at this early age in structural MRI (sMRI) due to a lack of myelination. Although this necessitates the acquisition of an additional sequence, the diffusion information improves the white matter segmentation throughout the brain, especially for the mid-brain structures such as the corpus callosum and the internal capsule. |
| Address |
Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA ; Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599 USA |
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English |
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0277-786X |
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| Notes |
PMID:26089584 |
Approved |
no |
| Call Number |
ref @ user @ |
Serial |
90511 |
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