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Advances in Computer Vision, Graphics, Image Processing and Pattern Recognition Techniques for MR Brain Cortical Segmentation and Reconstruction: A Review Toward functional MRI (fMRI)

  • Jasjit S. Suri
  • Sameer Singh
  • Xiaolan Zeng
  • Laura Reden
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

The importance of 2-D and 3-D brain segmentation has increased tremendously due to the recent growth in functional MRI (fMRI), perfusion-weighted imaging, diffusion-weighted imaging, volume graphics, 3-D segmentation, neurosurgical planning, navigation and MR brain scanning techniques. Besides that, recent growth in supervised and non-supervised brain segmentation techniques in 2-D (see Suri [322], Zavaljevski et al. [323], Barra et al. [324]) and 3-D (see Salle et al. [325], Kiebel et al. [326], Zeng et al. [327], Xu et al. [606], Fischl et al. [328], Linden et al. [329], Stokking [330], Smith [331], Hurdal [332] and ter Haar et al. [333]) have brought the engineering community, in areas such as computer vision, graphics, image processing (CVGIP) and pattern recognition, closer to the medical community, such as neuro-surgeons, psychiatrists, psychologists, physiologists, oncologists, radiologists and internists. This chapter is an attempt to review state-of-the-art cortical segmentation techniques in 2-D and 3-D using magnetic resonance imaging (MRI), and their applications. New challenges in this area are also discussed.

Keywords

Blood Oxygenation Level Dependent Segmentation Technique Mathematical Morphology Deformable Model Medical 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 London 2002

Authors and Affiliations

  • Jasjit S. Suri
  • Sameer Singh
  • Xiaolan Zeng
  • Laura Reden

There are no affiliations available

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