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Streamlining Cortical Surface Correction Process Using Automated Topological Tools

This study presents a novel approach to the automated correction of cortical surfaces through topological methods. The research, led by Monica K. Hurdal from the Department of Mathematics at Florida State University in Tallahassee, USA, focuses on enhancing the accuracy and efficiency of cortical surface analysis by implementing advanced automated corrections. By integrating topological principles, the algorithm offers a streamlined solution for identifying and rectifying errors in cortical surface models. The proposed method aims to improve the overall quality of cortical surface data for enhanced neuroimaging studies and computational modeling. For researchers and professionals in the field of neuroscience and brain mapping, this automated topological correction tool presents a valuable resource for optimizing cortical surface analysis processes.

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Streamlining Cortical Surface Correction Process Using Automated Topological Tools

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  1. Automated Topological Correction of Cortical Surfaces Monica K. Hurdal Department of Mathematics, Florida State University, Tallahassee, U.S.A.

  2. Automated Correction Surf Monica Department of Mathematics, Florida

  3. Topological of Corticalaces K. Hurdal State University, Tallahassee, U.S.A.

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