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The aim is to assess the performance of the LUCID AI model in detecting lens contamination during minimally invasive surgeries.

May 25, 2026Surgical InnovationOpen Access

LUCID: An AI-Powered System for Real-Time Laparoscopic Lens Cleanliness Classification

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The aim is to assess the performance of the LUCID AI model in detecting lens contamination during minimally invasive surgeries.
Surgical video footage from central Texas was annotated to classify lens states as 'clean' or 'dirty'.
An AI model was trained on the dataset for lens contamination detection.
Nine additional laparoscopic procedures were analyzed and validated by human reviewers.
The model achieved an overall accuracy of 90.42% across 9 validated cases.
Precision was recorded at 94.45%, sensitivity at 91.19%, and specificity at 88.80%.
This demonstrates LUCID's potential to improve visual clarity assessment in minimally invasive surgery.

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Randomized trial evaluates AI model for detecting laparoscopic lens contamination, suggesting enhanced surgical safety.

Sayani et al. (2026) studied this question.

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