Fuzzy thick rubber model for cerebral surface extraction in neonatal brain MR images

  • Authors:

  • Syoji Kobashi;Takuma Oshiba;Kumiko Ando;Reiichi Ishikura;Setsuro Imawaki;Shozo Hirota;Yutaka Hata

  • Affiliations:

  • Graduate School of Engineering, University of Hyogo, Hyogo, Japan and WPI Immunology Frontier Research Center;Graduate School of Engineering, University of Hyogo, Hyogo, Japan;Hyogo College of Medicine, Hyogo, Japan;Hyogo College of Medicine, Hyogo, Japan;Ishikawa Hospital, Japan;Hyogo College of Medicine, Hyogo, Japan;Graduate School of Engineering, University of Hyogo, Hyogo, Japan and WPI Immunology Frontier Research Center

  • Venue:
  • FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
  • Year:
  • 2009

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Abstract

Cerebral surface extraction plays a fundamental role of computer aided diagnosis (CAD) for neonatal brain magnetic resonance (MR) images. However, cerebral sulci of the neonatal brains is complexity folded, and it is difficult to extract complete cerebral contour from MR images due to the limitation of spatial resolution and partial volume effect (PVE). This paper proposes a novel method to extract the cerebral contour based on fuzzy thick rubber model (TRM). The TRM is deformed by using fuzzy control schemes so that the digitally synthesized MR images from the deforming TRM are identical to the given MR images. By synthesizing the MR images with respect to PVE, the proposed method is able to extract the cerebral contour with sub-voxel accuracy. The proposed method was applied to 7 subjects whose revised ages were from -17 days to 34 days. The root-mean-squared-error between the extracted contour and the manually delineated contour by two physicians was 1.09 ± 0.48 mm from the truth contour. And, to demonstrate the clinical effective, gyral index was calculated using the extracted cerebral contour.