Automated Segmentation of the Cerebellar Lobules Using Boundary Specific Classification and Evolution View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2013

AUTHORS

John A. Bogovic , Pierre-Louis Bazin , Sarah H. Ying , Jerry L. Prince

ABSTRACT

The cerebellum is instrumental in coordinating many vital functions ranging from speech and balance to eye movement. The effect of cerebellar pathology on these functions is frequently examined using volumetric studies that depend on consistent and accurate delineation, however, no existing automated methods adequately delineate the cerebellar lobules. In this work, we describe a method we call the Automatic Classification of Cerebellar Lobules Algorithm using Implicit Multi-boundary evolution (ACCLAIM). A multiple object geometric deformable model (MGDM) enables each boundary surface of each individual lobule to be evolved under different level set speeds. An important innovation described in this work is that the speed for each lobule boundary is derived from a classifier trained specifically to identify that boundary. We compared our method to segmentations obtained using the atlas-based and multi-atlas fusion techniques, and demonstrate ACCLAIM's superior performance. More... »

PAGES

62-73

References to SciGraph publications

  • 2005-07. Image Parsing: Unifying Segmentation, Detection, and Recognition in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2001-10. Random Forests in MACHINE LEARNING
  • 1997-02. Geodesic Active Contours in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2007. Digital Homeomorphisms in Deformable Registration in INFORMATION PROCESSING IN MEDICAL IMAGING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-38868-2_6

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    http://dx.doi.org/10.1007/978-3-642-38868-2_6

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/24683958


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