Automatic Segmentation of Putamen from Brain MRI

  • Yihui Liu
  • Bai Li
  • Dave Elliman
  • Paul Simon Morgan
  • Dorothee Auer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


In this paper we present an automatic segmentation of the Putamen shape from brain MRI based on wavelets and a neural network. Firstly we detect the Putamen region slice by slice using 1D wavelet feature extraction. Then fuzzy c-means technology is combined with edge detection to segment the objects inside the Putamen region. Finally features are extracted from the segmented objects and fed into a neural network classifier in order to identify the Putamen shape. Experiment shows the segmentation results to be accurate and efficient.


Brain Magnetic Resonance Image Automatic Segmentation Morphological Operation Canny Edge Detection Image Segmentation Technique 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yihui Liu
    • 1
    • 3
  • Bai Li
    • 1
  • Dave Elliman
    • 1
  • Paul Simon Morgan
    • 2
  • Dorothee Auer
    • 2
  1. 1.School of Computer Science & ITUniversity of NottinghamNottinghamUK
  2. 2.Academic RadiologyUniversity of Nottingham, Queen’s Medical CentreNottinghamUK
  3. 3.School of Computer ScienceShandong University of Light IndustryJinanChina

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