An Unified Reeb Analysis for Cortical Surface Reconstruction of Mri Images
Udayakumar E, Santhi S, Gowrishankar R, Shivkumar S and Sathish Kumar GDepartment of ECE, KIT-Kalaignarkarunanidhi Institute of Technology, Coimbatore, Tamilnadu, India.
Corresponding Author E-mail: udayakumar.sujith@gmail.comAbstract: This paper proposed an automated reconstruction of cortical surfaces using T1-weighted magnetic resonance images. A unified reeb analysis frame work has been used for the detection and removal of geometric and topological outliers on tissue boundaries. The system can pin point the position of spurious branches and topological outliers using intrinsic reed analysis. It is also used to rectify the tissue with confined filtering using information from both image intensity distributions and geometric regularity. For enhanced heftiness to image in homogeneity, and adaptive interpolation to attain sub-voxel accuracy in rebuilt surfaces, an enhanced tissue arrangement with Hessian features was developed using this system. A new system was designed by integrating these novel developments. The cortical surfaces with enhanced quality and vividly reduced computational cost when compared with the popular free surfer software can be automatically reconstructed using this system. The surfaces that well represent cortical anatomy and create thickness features with higher statistical power in population studies is shown in the presented work by comparing with free surfer.
Keywords: CT; MRI; CSF GM; LB; Reeb; Sulcal; and Back to TOC