Advances in computer vision, graphics, image processing and pattern recognition techniques for MR brain cortical segmentation and reconstruction: a review toward functional MRI (fMRI)

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.