Abstract
The sulci on the cerebral cortex are important anatomical landmarks and are frequently used for determining the surgical trajectory. We have previously developed a novel computer-based approach to assist in identifying the central sulcus from MR data of patients with various brain tumors based on only the anatomical features of the central sulcus which appeared to be quite efffective. Thus, our method provides accurate guidance for identifying the central sulcus. In our previous method, we extracted the sulci from Curved Planer Reformation (CPR) image, which is two-dimensional image reconstructed by unfolding the cortical surface and calculating whether their parameters matched the parameters of central sulcus. The sulcal extraction process is based on determining the minimum intensity regions, because sulci on T1-weighted MR images have the lowest signal intensity. However, when the sulci include vessel areas, the previous method is problematic: It cannot detect the minimum intensity area, because vessel areas have higher intensity than sulci areas, so the sulci are extracted as discontinuous lines. Therefore, we have improved the process for extracting sulci, taking the approach based on intensity of vessel areas among the sulci.