Schaer M Cuadra MB Tamarit L Lazeyras F Eliez S Thiran JP 2008 The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals. application/pdf https://sonar.ch/global/documents/240128 eng info:eu-repo/semantics/altIdentifier/doi/10.1109/TMI.2007.903576 info:eu-repo/semantics/altIdentifier/pmid/18334438 info:eu-repo/semantics/openAccess IEEE transactions on medical imaging. - 2008 Algorithms Artificial Intelligence Cerebral Cortex Child Computer Simulation Female Humans Image Enhancement Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Magnetic Resonance Imaging Male Models, Neurological Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity A surface-based approach to quantify local cortical gyrification. http://purl.org/coar/resource_type/c_6501