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Statistical shape model building method using surface registration and model prototype

Journal Article


Abstract


  • Automatic segmentation of organs from medical images is indispensable for the computer-assisted medical applications. Statistical Shape Models (SSMs) based scheme has been developed as an accurate and robust approach for extraction of anatomical structures, in which a crucial step is the need to place the sampled points (landmarks) with well corresponding across the whole training set. On the one hand, the correspondence of landmarks is related the quality of shape model. On the other hand, in clinical application some key positions of landmarks should be specified by physicians referring to the anatomic structure. In this paper, we develop an interactive method to build SSM that the landmark distribution can be modified manually without influencing the model quality. We extend an existing remeshing method to produce a model prototype in advance and surface features driven registration to insure the universal optimization of correspondence. The key landmarks are fixed during the prototype generation. We experimented and evaluated the proposed SSM method for lung regions, the deformations of which are considerable large.

Authors


  •   Li, Guangxu (external author)
  •   Wu, Jiaqi (external author)
  •   Xiao, Zhitao (external author)
  •   Kim, Hyoung (external author)
  •   Ogunbona, Philip O.

Publication Date


  • 2017

Citation


  • Li, G., Wu, J., Xiao, Z., Kim, H. & Ogunbona, P. (2017). Statistical shape model building method using surface registration and model prototype. Optics and Laser Technology, Online First 1-5.

Scopus Eid


  • 2-s2.0-85030029527

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/708

Number Of Pages


  • 4

Start Page


  • 1

End Page


  • 5

Volume


  • Online First

Place Of Publication


  • United Kingdom

Abstract


  • Automatic segmentation of organs from medical images is indispensable for the computer-assisted medical applications. Statistical Shape Models (SSMs) based scheme has been developed as an accurate and robust approach for extraction of anatomical structures, in which a crucial step is the need to place the sampled points (landmarks) with well corresponding across the whole training set. On the one hand, the correspondence of landmarks is related the quality of shape model. On the other hand, in clinical application some key positions of landmarks should be specified by physicians referring to the anatomic structure. In this paper, we develop an interactive method to build SSM that the landmark distribution can be modified manually without influencing the model quality. We extend an existing remeshing method to produce a model prototype in advance and surface features driven registration to insure the universal optimization of correspondence. The key landmarks are fixed during the prototype generation. We experimented and evaluated the proposed SSM method for lung regions, the deformations of which are considerable large.

Authors


  •   Li, Guangxu (external author)
  •   Wu, Jiaqi (external author)
  •   Xiao, Zhitao (external author)
  •   Kim, Hyoung (external author)
  •   Ogunbona, Philip O.

Publication Date


  • 2017

Citation


  • Li, G., Wu, J., Xiao, Z., Kim, H. & Ogunbona, P. (2017). Statistical shape model building method using surface registration and model prototype. Optics and Laser Technology, Online First 1-5.

Scopus Eid


  • 2-s2.0-85030029527

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/708

Number Of Pages


  • 4

Start Page


  • 1

End Page


  • 5

Volume


  • Online First

Place Of Publication


  • United Kingdom