Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Multiresolution signal processing for meshes
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A Digital Brain Atlas for Surgical Planning, Model-Driven Segmentation, and Teaching
IEEE Transactions on Visualization and Computer Graphics
Multisubject Non-rigid Registration of Brain MRI Using Intensity and Geometric Features
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Automatic Recognition of Cortical Sulci Using a Congregation of Neural Networks
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Removing excess topology from isosurfaces
ACM Transactions on Graphics (TOG)
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We propose to match a labeled mesh onto the patient brain surface in a multiresolution way for labeling the patient brain. Labeling the patient brain surface provides a map of the brain folds where the neuroradiologist and the neurosurgeon can easily track the features of interest. Due to the complexity of the cortical surface, this task usually depends on the intervention of an expert, and is time-consuming. Our multiresolution representation for the brain surface allows the automated classification of the folds based on their size. The atlas mesh is deformed from coarse to fine to robustly capture the patient brain folds from the largest to the smallest. Once the atlas mesh matches the patient mesh, the atlas labels are transferred to the patient mesh, and color coded for visualization.