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Atlas Guided Identification of Brain Structures by Combining 3D Segmentation and SVM Classification

  • Ayelet Akselrod-Ballin
  • Meirav Galun
  • Moshe John Gomori
  • Ronen Basri
  • Achi Brandt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

This study presents a novel automatic approach for the identification of anatomical brain structures in magnetic resonance images (MRI). The method combines a fast multiscale multi-channel three dimensional (3D) segmentation algorithm providing a rich feature vocabulary together with a support vector machine (SVM) based classifier. The segmentation produces a full hierarchy of segments, expressed by an irregular pyramid with only linear time complexity. The pyramid provides a rich, adaptive representation of the image, enabling detection of various anatomical structures at different scales. A key aspect of the approach is the thorough set of multiscale measures employed throughout the segmentation process which are also provided at its end for clinical analysis. These features include in particular the prior probability knowledge of anatomic structures due to the use of an MRI probabilistic atlas. An SVM classifier is trained based on this set of features to identify the brain structures. We validated the approach using a gold standard real brain MRI data set. Comparison of the results with existing algorithms displays the promise of our approach.

Keywords

Support Vector Machine Gray Matter Magnetic Resonance Image Data Candidate Segment Magnetic Resonance Image Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ayelet Akselrod-Ballin
    • 1
  • Meirav Galun
    • 1
  • Moshe John Gomori
    • 2
  • Ronen Basri
    • 1
  • Achi Brandt
    • 1
  1. 1.Dept. of Computer Science and Applied MathWeizmann Institute of ScienceRehovotIsrael
  2. 2.Dept. of RadiologyHadassah University HospitalJerusalemIsrael

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