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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 11389
School of Cognitive Sciences
  Title:   Effect of the Number of Coupled Structures on the Segmentation of Brain Structures from MRI
1 . A. Akhondi-Asl
2 . Hamid Soltanianzadeh
  Status:   In Proceedings
  Proceeding: Presented at and Published in the Proceedings of the 16th Iranian Conference on Elec. Eng. (ICEE?08), Tehran, Iran, May 13-15, 2008
  Year:  2008
  Supported by:  IPM
We propose a three-dimensional,nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capturestructural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, analytical derivatives are used to improve speed and accuracy. Quantitative results show the improvement in the segmentation quality due to the integration of the coupling information into the segmentation process.

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