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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 Type Journal Article
Year 2015 Publication Proceedings of SPIE--the International Society for Optical Engineering Abbreviated Journal Proc SPIE Int Soc Opt Eng
Volume (down) 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 90669
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Author Vachet, C.; Yvernault, B.; Bhatt, K.; Smith, R.G.; Gerig, G.; Hazlett, H.C.; Styner, M.
Title Automatic corpus callosum segmentation using a deformable active Fourier contour model Type Journal Article
Year 2012 Publication Proceedings of SPIE--the International Society for Optical Engineering Abbreviated Journal Proc SPIE Int Soc Opt Eng
Volume (down) 8317 Issue Pages
Keywords Fourier coefficient; corpus callosum; segmentation; shape model
Abstract The corpus callosum (CC) is a structure of interest in many neuroimaging studies of neuro-developmental pathology such as autism. It plays an integral role in relaying sensory, motor and cognitive information from homologous regions in both hemispheres. We have developed a framework that allows automatic segmentation of the corpus callosum and its lobar subdivisions. Our approach employs constrained elastic deformation of flexible Fourier contour model, and is an extension of Szekely's 2D Fourier descriptor based Active Shape Model. The shape and appearance model, derived from a large mixed population of 150+ subjects, is described with complex Fourier descriptors in a principal component shape space. Using MNI space aligned T1w MRI data, the CC segmentation is initialized on the mid-sagittal plane using the tissue segmentation. A multi-step optimization strategy, with two constrained steps and a final unconstrained step, is then applied. If needed, interactive segmentation can be performed via contour repulsion points. Lobar connectivity based parcellation of the corpus callosum can finally be computed via the use of a probabilistic CC subdivision model. Our analysis framework has been integrated in an open-source, end-to-end application called CCSeg both with a command line and Qt-based graphical user interface (available on NITRC). A study has been performed to quantify the reliability of the semi-automatic segmentation on a small pediatric dataset. Using 5 subjects randomly segmented 3 times by two experts, the intra-class correlation coefficient showed a superb reliability (0.99). CCSeg is currently applied to a large longitudinal pediatric study of brain development in autism.
Address Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA ; Department of Computer Sciences, University of North Carolina at Chapel Hill, NC, 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 1018-4732 ISBN Medium
Area Expedition Conference
Notes PMID:24353382 Approved no
Call Number ref @ user @ Serial 90515
Permanent link to this record
 

 
Author Vachet, C.; Yvernault, B.; Bhatt, K.; Smith, R.G.; Gerig, G.; Hazlett, H.C.; Styner, M.
Title Automatic corpus callosum segmentation using a deformable active Fourier contour model Type Journal Article
Year 2012 Publication Proceedings of SPIE--the International Society for Optical Engineering Abbreviated Journal Proc SPIE Int Soc Opt Eng
Volume (down) 8317 Issue Pages
Keywords Fourier coefficient; corpus callosum; segmentation; shape model
Abstract The corpus callosum (CC) is a structure of interest in many neuroimaging studies of neuro-developmental pathology such as autism. It plays an integral role in relaying sensory, motor and cognitive information from homologous regions in both hemispheres. We have developed a framework that allows automatic segmentation of the corpus callosum and its lobar subdivisions. Our approach employs constrained elastic deformation of flexible Fourier contour model, and is an extension of Szekely's 2D Fourier descriptor based Active Shape Model. The shape and appearance model, derived from a large mixed population of 150+ subjects, is described with complex Fourier descriptors in a principal component shape space. Using MNI space aligned T1w MRI data, the CC segmentation is initialized on the mid-sagittal plane using the tissue segmentation. A multi-step optimization strategy, with two constrained steps and a final unconstrained step, is then applied. If needed, interactive segmentation can be performed via contour repulsion points. Lobar connectivity based parcellation of the corpus callosum can finally be computed via the use of a probabilistic CC subdivision model. Our analysis framework has been integrated in an open-source, end-to-end application called CCSeg both with a command line and Qt-based graphical user interface (available on NITRC). A study has been performed to quantify the reliability of the semi-automatic segmentation on a small pediatric dataset. Using 5 subjects randomly segmented 3 times by two experts, the intra-class correlation coefficient showed a superb reliability (0.99). CCSeg is currently applied to a large longitudinal pediatric study of brain development in autism.
Address Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA ; Department of Computer Sciences, University of North Carolina at Chapel Hill, NC, 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 1018-4732 ISBN Medium
Area Expedition Conference
Notes PMID:24353382 Approved no
Call Number ref @ user @ Serial 90673
Permanent link to this record
 

 
Author Slabý, T.; Antoa, M.; Dostál, Z.\vek; Kolman, P.; Chmelík, R.
Title Coherence-controlled holographic microscope Type Journal Article
Year 2010 Publication Quantum Abbreviated Journal
Volume (down) 7746 Issue Pages 77461-77461
Keywords diffraction grating,digital holographic microscope,measurement,off-axis achromatic interferometer,phase object,quantitative phase contrast
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number refbase @ admin @ Slaby2010 Serial 5634
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Author Tý , M.\vej; Chmelík, R.
Title Numerical refocusing of planar samples unlimited Type Journal Article
Year 2010 Publication Quantum Abbreviated Journal
Volume (down) 7746 Issue Pages 774620-774620
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number refbase @ admin @ Tyc2010 Serial 5693
Permanent link to this record