Computational NeuroscienceAutomated interhemispheric surface extraction in T1-weighted MRI using intensity and symmetry information

- The whole head is divided with a max-flow/min-cut optimized surface.
- Both intensity and symmetry information is used for the surface optimization.
- No time consuming preprocessing steps are required.
- The interhemispheric surface is extracted in less than 30 s.

BackgroundLocalizing the human interhemispheric region is of interest in image analysis mainly because it can be used for hemisphere separation and as a preprocessing step for interhemispheric structure localization. Many existing methods focus on only one of these applications.New methodHere a new Intensity and Symmetry based Interhemispheric Surface extraction method (ISIS) that enables both applications is presented. A combination of voxel intensity and local symmetry is used to optimize a surface from T1-weighted MRI.ResultsISIS was evaluated in regard to cerebral hemisphere separation using manual segmentations. It was also evaluated in regard to being a preprocessing step for interhemispheric structure localization using manually placed landmarks.Comparison with existing methodsResults were compared to cerebral hemisphere separations by BrainVisa and Freesurfer as well as to a midsagittal plane (MSP) extraction method. ISIS had less misclassified voxels than BrainVisa (ISIS: 0.119 ± 0.114%, BrainVisa: 0.138 ± 0.084%, p = 0.020). Freesurfer had less misclassified voxels than ISIS for one dataset (ISIS: 0.063 ± 0.056%, Freesurfer: 0.049 ± 0.044%, p = 0.019), but failed to produce usable results for another. Total voxel distance from all manual landmarks did not differ significantly between ISIS and the MSP method (ISIS: 4.00 ± 1.88, MSP: 4.47 ± 4.97).ConclusionsISIS was found successful in both cerebral hemisphere separation and as a preprocessing step for interhemispheric structure localization. It needs no time consuming preprocessing and extracts the interhemispheric surface in less than 30 s.