Sulcal and gyral landmarks on the human cerebral cortex are required for various studies of the human brain. Whether used directly to examine sulcal geometry, or indirectly to drive cortical surface registration methods, the accuracy of these landmarks is essential. While several methods have been developed to automatically identify sulci and gyri, their accuracy may be insufficient for certain neuroanatomical studies. We describe a semi-automated procedure that delineates a sulcus or gyrus given a limited number of user-selected points. The method uses a graph theory approach to identify the lowest-cost path between the points, where the cost is a combination of local curvature features and the distance between vertices on the surface representation. We implemented the algorithm in an interface that guides the user through a cortical surface delineation protocol, and we incorporated this tool into our BrainSuite software. We performed a study to compare the results produced using our method with results produced using Display, a popular tool that has been used extensively for manual delineation of sulcal landmarks. Six raters were trained on the delineation protocol. They performed delineations on 12 brains using both software packages. We performed a statistical analysis of 3 aspects of the delineation task: time required to delineate the surface, registration accuracy achieved compared to an expert-delineated gold-standard, and variation among raters. Our new method was shown to be faster to use, to provide reduced inter-rater variability, and to provide results that were at least as accurate as those produced using Display.