Landmark correspondence optimization for coupled surfaces

  • Authors:
  • Lin Shi;Defeng Wang;Pheng Ann Heng;Tien-Tsin Wong;Winnie C. W. Chu;Benson H. Y. Yeung;Jack C. Y. Cheng

  • Affiliations:
  • Department of Computer Science and Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Computer Science and Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Computer Science and Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Computer Science and Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Diagnostic Radiology and Organ Imaging, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China;Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China

  • Venue:
  • MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
  • Year:
  • 2007

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Abstract

Volumetric layers are often encountered in medical images. Unlike solid structures, volumetric layers are characterized by double and nested bounding surfaces. It is expected that better statistical models can be built by utilizing the surface coupleness rather than simply applying the landmarking method on each of them separately. We propose an approach to optimizing the landmark correspondence on the coupled surfaces by minimizing the description length that incorporates local thickness gradient. The evaluations are performed on a set of 2-D synthetic close coupled contours and a set of real-world open surfaces, the skull vaults. Compared with performing landmarking separately on the coupled surfaces, the proposed method constructs models that have better generalization ability and specificity.