Tech rep on medical image segmentation

[DeLiang Wang]

  The following technical report is available on medical image 
  segmentation. Comments and suggestions are welcome
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                 Segmentation of Medical Images Using LEGION

                 Technical Report: OSU-CISRC-4/97-TR26, 1997
  
                Naeem Shareef, DeLiang L. Wang and Roni Yagel
                Department of Computer and Information Science
                         The Ohio State University
                         Columbus, Ohio 43210, USA 
 
  
                                  ABSTRACT
  
   Advances in computer and visualization technology allow clinicians to 
   virtually interact with anatomical structures contained within sampled 
   medical image datasets. A hindrance to the effective use of this technology 
   is the problem of image segmentation. In this paper, we utilize a recently 
   proposed oscillator network called LEGION (Locally Excitatory Globally 
   Inhibitory Oscillator Network), whose ability to achieve fast synchrony with 
   local excitation and desynchrony with global inhibition makes it an effective
   computational framework for grouping similar features 
   and segregating dissimilar ones in an image. We describe an image 
   segmentation algorithm derived from LEGION and introduce an adaptive scheme 
   to  choose tolerances. We show results of the algorithm to 2D and 3D (volume)
   CT  and MRI medical image datasets, and compare our results with manual 
   segmentation. LEGION's computational and architectural properties make it a 
   promising approach for real-time medical image segmentation using multiple 
   features.
  
  
  A Postscript version of the report is available via ftp at 
  FTP-host    : ftp.cis.ohio-state.edu
  FTP-pathname: pub/tech-report/1997/TR26-DIR/
 
  OR
 
  an HTML version can be found at 
  HTML version: http://www.cis.ohio-state.edu/~shareef/OSUTR26/journal-1.html
  
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