Lissajous confocal laser endomicroscopy (CLE) is a promising solution for high speed in vivo optical biopsy for handheld scenarios. However, Lissajous scanning traces a resonant trajectory and samples only the visited pixels per frame; at high frame rates, many pixels remain unvisited, creating structured holes. In this work, we introduce the first benchmark for high-rate Lissajous CLE, consisting of low-quality video clips paired with high-quality reference images. The reference images are wide-FOV mosaics obtained by stitching stabilized, slow-scan frames of the same tissue, enabling temporally aligned supervision. Using this dataset, we propose MIRA, a lightweight recurrent framework for Lissajous CLE restoration that iteratively aggregates temporal context through feature reuse and displacement alignment. Our experiments demonstrate that MIRA outperforms both lightweight and high-complexity baselines in restoration quality while maintaining a favorable computational efficiency suitable for clinical deployment.
@article{arxiv.2605.00527,
title = {Multi-frame Restoration for High-rate Lissajous Confocal Laser Endomicroscopy},
author = {Minhee Lee and Sangyoon Lee and Jiwook Lee and Minki Hong and Kyuyoung Kim and Won Hwa Kim and Jaeho Lee},
journal= {arXiv preprint arXiv:2605.00527},
year = {2026}
}