Relevance-Based Compression of Cataract Surgery Videos

TL;DR

This paper introduces a relevance-based video compression method tailored for cataract surgery videos, significantly reducing storage needs while maintaining quality, evaluated with expert feedback and multiple codecs.

Contribution

It presents a novel relevance-based compression scheme leveraging domain-specific information for cataract surgery videos, improving storage efficiency over standard codecs.

Findings

Up to 98.82% compression savings with AV1 codec.

Significant quality preservation confirmed by medical experts.

Effective compression across multiple state-of-the-art codecs.

Abstract

In the last decade, the need for storing videos from cataract surgery has increased significantly. Hospitals continue to improve their imaging and recording devices (e.g., microscopes and cameras used in microscopic surgery, such as ophthalmology) to enhance their post-surgical processing efficiency. The video recordings enable a lot of user-cases after the actual surgery, for example, teaching, documentation, and forensics. However, videos recorded from operations are typically stored in the internal archive without any domain-specific compression, leading to a massive storage space consumption. In this work, we propose a relevance-based compression scheme for videos from cataract surgery, which is based on content specifics of particular cataract surgery phases. We evaluate our compression scheme with three state-of-the-art video codecs, namely H.264/AVC, H.265/HEVC, and AV1, and ask medical experts to evaluate the visual quality of encoded videos. Our results show significant savings, in particular up to 95.94% when using H.264/AVC, up to 98.71% when using H.265/HEVC, and up to 98.82% when using AV1.