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Morphometric Analysis for Pathological Abnormality Detection in the Skull Vaults of Adolescent Idiopathic Scoliosis Girls

  • Lin Shi
  • Pheng Ann Heng
  • Tien-Tsin Wong
  • Winnie C. W. Chu
  • Benson H. Y. Yeung
  • Jack C. Y. Cheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

In this paper, we present a comprehensive framework to detect morphological changes in skull vaults of adolescent idiopathic scoliosis girls. To our knowledge, this is the first attempt to use a combination of medical knowledge, image analysis techniques, statistical learning tools, and scientific visualization methods to detect skull morphological changes. The shape analysis starts from a reliable 3-D segmentation of the skull using thresholding and math-morphological operations. The gradient vector flow is used to model the skull vault surface, which is followed by a spherically uniform sampling. The scale-normalized distances from the shape centroid to sample points are defined as the features. The most discriminative features are selected using recursive feature elimination for support vector machine. The results of this study specify the skull vault surface changes and shed light on building the evidence of bone formation abnormality in AIS girls.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lin Shi
    • 1
    • 2
  • Pheng Ann Heng
    • 1
    • 2
  • Tien-Tsin Wong
    • 1
    • 2
  • Winnie C. W. Chu
    • 3
  • Benson H. Y. Yeung
    • 4
  • Jack C. Y. Cheng
    • 4
  1. 1.Department of Computer Science and EngineeringThe Chinese University of Hong KongHong KongChina
  2. 2.Shun Hing Institute of Advanced EngineeringThe Chinese University of Hong KongHong KongChina
  3. 3.Department of Diagnostic Radiology and Organ ImagingThe Chinese University of Hong KongHong KongChina
  4. 4.Department of Orthopaedics and TraumatologyThe Chinese University of Hong KongHong KongChina

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