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Author (up) Cherel, M.; Budin, F.; Prastawa, M.; Gerig, G.; Lee, K.; Buss, C.; Lyall, A.; Consing, K.Z.; Styner, M. url  openurl
  Title Automatic Tissue Segmentation of Neonate Brain MR Images with Subject-specific Atlases Type Journal Article
  Year 2015 Publication Proceedings of SPIE--the International Society for Optical Engineering Abbreviated Journal Proc SPIE Int Soc Opt Eng  
  Volume 9413 Issue Pages  
  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  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0277-786X ISBN Medium  
  Area Expedition Conference  
  Notes PMID:26089584 Approved no  
  Call Number ref @ user @ Serial 90511  
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