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Biennial International Conference on Information Processing in Medical Imaging

IPMI 1997: Information Processing in Medical Imaging pp 99–112Cite as

Automated segmentation of brain exterior in MR images driven by empirical procedures and anatomical knowledge

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1230))

Abstract

This work demonstrates encouraging initial results for increasing the automation of a practical and precise MR brain image segmentation method. The intensity threshold for segmenting the brain exterior is automatically determined by locating the choroid plexus. This is done by finding peaks in a series of histograms taken over regions specified using anatomical knowledge. Intensity inhomogeneities are accounted for by adjusting the global intensity to match the white matter peak intensity in local regions. The results from 20 different brain scans (over 1000 images) obtained under different conditions are presented to validate the method which was able to determine the appropriate threshold in approximately 80% of the data.

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Authors and Affiliations

  1. Center for Morphometric Analysis, Neuroscience Center, Massachusetts General Hospital, CNY-6, Building 149, 13th St., 02129-2000, Charlestown, MA, USA

    Andrew J. Worth, Nikos Makris, James W. Meyer, Verne S. Caviness Jr. & David N. Kennedy

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  1. Andrew J. Worth
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  2. Nikos Makris
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  3. James W. Meyer
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  4. Verne S. Caviness Jr.
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  5. David N. Kennedy
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James Duncan Gene Gindi

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© 1997 Springer-Verlag Berlin Heidelberg

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Worth, A.J., Makris, N., Meyer, J.W., Caviness, V.S., Kennedy, D.N. (1997). Automated segmentation of brain exterior in MR images driven by empirical procedures and anatomical knowledge. In: Duncan, J., Gindi, G. (eds) Information Processing in Medical Imaging. IPMI 1997. Lecture Notes in Computer Science, vol 1230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63046-5_8

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  • DOI: https://doi.org/10.1007/3-540-63046-5_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63046-3

  • Online ISBN: 978-3-540-69070-2

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