| dc.description.abstract | Before undergoing brain surgery, surgeons can only rely on the patient’s medical anatomical images, such as computerized tomography (CT) or magnetic resonance imaging (MRI), and their knowledge to plan surgical paths. However, 2D images can provide limited information. If 3D models of brain functional areas and white matter nerve fibers can be provided, it can help surgeons plan safer surgical paths.
This research includes 3D model reconstruction of cortical functional areas and white matter nerve fibers, image alignment, and region of interest (ROI) setting of neural model around the tumor. MRI images are used to identify functional areas and then reconstruct cortical functional area models. Different nerve fiber tracking algorithms are applied to generate white matter nerve fibers using DTI images and their correctness of reconstructed nerve fibers is compared. The coordinate frames of cortical functional areas and white matter nerve fibers are converted and aligned with MRI images coordinate frame. Then the surgeon can plan a safe surgical path based on the fused images.
By comparing with anatomical features, the constructed cortex functional area model shows that important functional areas have been completely reconstructed and identified. The white matter nerve fiber model is confirmed for the integrity of the superior, inferior longitudinal fasciculus, the uncinate fasciculus, the arcuate fasciculus, the inferior occipitofrontal fasciculus, the cingulate fasciculus, the corona radiata, and the corpus callosum. The results show that the Tensorline algorithm is much better. The alignment accuracy of cortical functional area images and MRI images is evaluated by using the checkerboard classification method. The results show that the brain outline, white matter, gray matter, and tumors are all connected smoothly, so it can be inferred that the alignment accuracy is reliable. | en_US |