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Template-Based Cortical Surface Reconstruction With Minimal Energy Deformation

MCML Authors

Fabian Bongratz

→ Group Christian Wachinger
Artificial Intelligence in Medical Imaging

Christian Wachinger

Prof. Dr.

Principal Investigator

Artificial Intelligence in Medical Imaging

Abstract

Cortical surface reconstruction (CSR) from magnetic resonance imaging (MRI) is fundamental to neuroimage analysis, enabling morphological studies of the cerebral cortex and functional brain mapping. Recent advances in learning-based CSR have dramatically accelerated processing, allowing for reconstructions through the deformation of anatomical templates within seconds. However, ensuring the learned deformations are optimal in terms of deformation energy and consistent across training runs remains a particular challenge. In this work, we design a Minimal Energy Deformation (MED) loss, acting as a regularizer on the deformation trajectories and complementing the widely used Chamfer distance in CSR. We incorporate it into the recent V2C-Flow model and demonstrate considerable improvements in previously neglected training consistency and reproducibility without harming reconstruction accuracy and topological correctness.

inproceedings

ShapeMI @MICCAI 2025

Workshop on Shape in Medical Imaging at the 28th International Conference on Medical Image Computing and Computer Assisted Intervention. Daejeon, Republic of Korea, Sep 23-27, 2025.