English

Enhancing 3T Retinotopic Maps Using Diffeomorphic Registration

Image and Video Processing 2024-05-06 v1

Abstract

Retinotopic mapping aims to uncover the relationship between visual stimuli on the retina and neural responses on the visual cortical surface. This study advances retinotopic mapping by applying diffeomorphic registration to the 3T NYU retinotopy dataset, encompassing analyze-PRF and mrVista data. Diffeomorphic Registration for Retinotopic Maps (DRRM) quantifies the diffeomorphic condition, ensuring accurate alignment of retinotopic maps without topological violations. Leveraging the Beltrami coefficient and topological condition, DRRM significantly enhances retinotopic map accuracy. Evaluation against existing methods demonstrates DRRM's superiority on various datasets, including 3T and 7T retinotopy data. The application of diffeomorphic registration improves the interpretability of low-quality retinotopic maps, holding promise for clinical applications.

Keywords

Cite

@article{arxiv.2405.01552,
  title  = {Enhancing 3T Retinotopic Maps Using Diffeomorphic Registration},
  author = {Negar Jalili-Mallak and Yanshuai Tu and Zhong-Lin Lu and Yalin Wang},
  journal= {arXiv preprint arXiv:2405.01552},
  year   = {2024}
}

Comments

5 pages, 1 figures, 2 tables, 2024 IEEE International Symposium on Biomedical Imaging

R2 v1 2026-06-28T16:14:36.078Z