Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system.

The training set comprised 4308 frames (41,066 labels); the internal testing set, 1803 frames (17,211 labels); and the external validation set, 721 frames (6685 labels).

Training performance reached box precision 0.896, recall 0.891, mAP@50 0.937, and AP@[0.50-0.95] 0.846; mask AP@[0.50-0.95] was 0.809.

On the internal testing set, box AP@[0.50-0.95] was 0.670 and mask AP@[0.50-0.95] 0.642.

The NASA-TLX score was 26.72±6.51, indicating low cognitive burden, and the System Usability Scale score was 78.33±5.20, demonstrating good usability.