Multi-frame Restoration for High-rate Lissajous Confocal Laser Endomicroscopy
For clinicians using high-speed Lissajous CLE, this work provides a practical restoration method to improve image quality without sacrificing speed.
This work introduces the first benchmark for high-rate Lissajous confocal laser endomicroscopy (CLE) restoration and proposes MIRA, a lightweight recurrent framework that outperforms baselines in restoration quality while maintaining computational efficiency suitable for clinical deployment.
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.