A01-KB110 Disorder Development Onset Prediction Based on Spatiotemporal Statistical Shape Model

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Member

  • Primary Investigator
    Syoji Kobashi (University of Hyogo, Graduate School of Engineering, Professor)
  • Corporative Researcher
    Kumiko Ando (Hyogo College of Medicine, School of Medicine, Associate Professor)
    Reiichi Ishikura (Hyogo College of Medicine, School of Medicine, Associate Professor)


Overview

In Japan, almost 10 % of population is development disorder, and it becomes a serious problem. And, about 10 % of neonates are low- birth-weight-babies, and there are strong correlation with onset of development disorder. Although it is well known that early intervention to development disorder is effective, the intervention has been applied to after finding development disorder on school-age children because of lack of onset prediction method and expensive intervention cost. In this specific research area, there are many studies on statistical shape model, however, it is still underdevelopment on spatiotemporal statistical shape model for neonatal brain.

The objective of this study is to find a relationship between development disorder and neonatal brain morphology, and to establish an onset prediction method using neonatal brain MR images. The method extracts morphological features and its temporal changes with growing by using the spatiotemporal statistical shape model. This study will contribute multi-disciplinary of this special area by extending statistical shape model in temporal domain, and by introducing a new application of the spatiotemporal statistical shape odel.

Project Design

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