ArticleCureus2026
A Pilot Study on the Efficacy of Artificial Intelligence-Driven Monocular Three-Dimensional Conversion for Endoscopic Spatial Perception.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMonocular two-dimensional endoscopes inherently lack depth perception, significantly increasing the cognitive load during surgical procedures. Artificial intelligence has the potential to convert two-dimensional video feeds into stereoscopic three-dimensional views in real time, yet its depth-dependent limitations remain underexplored. This pilot study evaluated the efficacy and spatial limitations of an artificial intelligence-driven monocular three-dimensional conversion system.
methodsSix participants performed a surgical target-grasping task within a dry box simulator under three distinct visual conditions: a monocular two-dimensional baseline, an artificial intelligence-generated three-dimensional system, and a native stereoscopic three-dimensional system. Targets were placed at three specific working distances of 3 cm, 5 cm, and 10 cm, yielding a total of 90 independent trials.
resultsThe overall grasping success rate was 33.3% for the two-dimensional baseline, 52.2% for the artificial intelligence system, and 68.9% for the native three-dimensional system. Statistical analysis confirmed that the artificial intelligence conversion significantly improved the success rate over the standard two-dimensional environment. Furthermore, the artificial intelligence system drastically reduced the average task completion time to 5.25 seconds compared to 7.93 seconds in the two-dimensional setting. A distance-based sub-analysis revealed a notable physical limitation. The artificial intelligence system provided exceptional spatial support, comparable to native three-dimensional systems, at close working distances of 3 cm and 5 cm. However, at a deeper distance of 10 cm, the monocular depth cues diminished, leading to a decline in estimation accuracy.
conclusionsReal-time artificial intelligence-driven three-dimensional conversion successfully enhances spatial perception and operational efficiency in surgical environments. While it serves as a highly effective visual assist tool at standard close working distances, operators must remain aware of its limitations in deeper operative spaces.
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