Exploring Temporal Constraints for Unsupervised Iris Motion Tracking in AS-OCT Videos
Lingxi Hu, Xiao Wu, Risa Higashita, Xiaoli Xing, Menglan Zhou, Song Lin, Xiaorong Li, Xiaoling Li
Abstract
Iris motion tracking is critical for discriminating the iris stiffness and developmental stage of primary angle-closure disease (PACD). Anterior segment optical coherence tomography (AS-OCT) video is a highly efficient approach to observe the morphological determinant in iris motion. However, the iris exhibits inconsistent elastic changes during movement, accompanied by changes in local features after long-term frames. Currently, iris tracking methods have not yet been studied in AS-OCT videos. In this paper, we propose a Temporal Constraint-based Tracking Morph (TCTMorph) for estimating iris trajectory in long-term AS-OCT videos. We first estimate the deformation fields between three interrelated frames by a multi-frame diffeomorphic registration network. Then, we estimate iris trajectory from these results in long-term AS-OCT video sequences by leveraging temporal constraints among the consecutive flows. Our experiments on multi-center AS-OCT glaucoma datasets demonstrate that our method outperforms conventional motion tracking methods for long-term iris trajectory tracking.
BibTeX
@inproceedings{icassp2025_exploringtempora,
title = {Exploring Temporal Constraints for Unsupervised Iris Motion Tracking in AS-OCT Videos},
author = {Lingxi Hu and Xiao Wu and Risa Higashita and Xiaoli Xing and Menglan Zhou and Song Lin and Xiaorong Li and Xiaoling Li and Jinming Duan and Jiang Liu},
booktitle = {ICASSP 2025},
year = {2025}
}