Title: Machine Vision-Based Surgical Lighting System:Design and Implementation Show Chinese title

Title: 基于机器视觉的手术照明系统：设计与实现

Abstract: Effortless and ergonomically designed surgical lighting is critical for precision and safety during procedures. However, traditional systems often rely on manual adjustments, leading to surgeon fatigue, neck strain, and inconsistent illumination due to drift and shadowing. To address these challenges, we propose a novel surgical lighting system that leverages the YOLOv11 object detection algorithm to identify a blue marker placed above the target surgical site. A high-power LED light source is then directed to the identified location using two servomotors equipped with tilt-pan brackets. The YOLO model achieves 96.7% mAP@50 on the validation set consisting of annotated images simulating surgical scenes with the blue spherical marker. By automating the lighting process, this machine vision-based solution reduces physical strain on surgeons, improves consistency in illumination, and supports improved surgical outcomes. Show Chinese abstract

Abstract: 高效且符合人体工程学设计的手术照明对于手术过程中的精确性和安全性至关重要。 然而，传统系统通常依赖手动调整，导致外科医生疲劳、颈部不适以及由于漂移和阴影造成的不一致照明。 为了解决这些挑战，我们提出了一种新颖的手术照明系统，该系统利用YOLOv11目标检测算法来识别放置在目标手术部位上方的蓝色标记。 然后使用配备俯仰-平转支架的两个伺服电机将高功率LED光源引导至识别的位置。 YOLO模型在包含模拟手术场景中带有蓝色球形标记的注释图像的验证集上实现了96.7%的mAP@50。 通过自动化照明过程，这种基于机器视觉的解决方案减轻了外科医生的体力负担，提高了照明的一致性，并有助于改善手术结果。