Vertex Correspondence in Cortical Surface Reconstruction

Rickmann, Anne-Marie ; Bongratz, Fabian und Wachinger, Christian (2023): Vertex Correspondence in Cortical Surface Reconstruction. 26th International Conference on Medical Image Computing and Computer Assisted Intervention, Vancouver, Canada, October 8-12, 2023. Greenspan, Hayit; Madabhushi, Anant; Mousavi, Parvin; Salcudean, Septimiu; Duncan, James; Syeda-Mahmood, Tanveer und Taylor, Russell (eds.) : In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, Vol. 14227 Cham: Springer. pp. 318-327

Abstract

Mesh-based cortical surface reconstruction is a fundamental task in neuroimaging that enables highly accurate measurements of brain morphology. Vertex correspondence between a patient’s cortical mesh and a group template is necessary for comparing cortical thickness and other measures at the vertex level. However, post-processing methods for generating vertex correspondence are time-consuming and involve registering and remeshing a patient’s surfaces to an atlas. Recent deep learning methods for cortex reconstruction have neither been optimized for generating vertex correspondence nor have they analyzed the quality of such correspondence. In this work, we propose to learn vertex correspondence by optimizing an L1 loss on registered surfaces instead of the commonly used Chamfer loss. This results in improved inter- and intra-subject correspondence suitable for direct group comparison and atlas-based parcellation. We demonstrate that state-of-the-art methods provide insufficient correspondence for mapping parcellations, highlighting the importance of optimizing for accurate vertex correspondence.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: Medicine > Medical Center of the University of Munich > Clinic and Polyclinic for Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science; 600 Technology > 610 Medicine and health
• ISBN: 978-3-031-43992-6 ; 978-3-031-43993-3
• Place of Publication: Cham
• Annotation: Teil von: International Conference on Medical Image Computing and Computer-Assisted Intervention ; Lecture Notes in Computer Science (LNCS, Band 14227)
• Language: English