A path-planning algorithm for image-guided neurosurgery

A computer algorithm for determining optimal surgical paths in the brain is presented. The algorithm computes a cost function associated with each point on the outer brain boundary, which is treated as a candidate entry point. The cost function is determined partly based on a segmentation of the patients images into gray and white matter, and partly based on a spatially transformed atlas of the human brain registered to the patient's MR images. The importance of various structures , such as thalamic nuclei, optic nerve and radiations, and individual Brodman's areas, can be deened on the atlas and transferred onto the patient's images through the spatial transformation. The cost of a particular path associated with each critical structure, as well as the total cost of each path are computed and displayed, allowing the surgeon to deene a low cost path, to visualize an arbitrary cross-section through the patient's MR images that contains this path, and to examine all the cross-sectional images orthogonal to that path.