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在腹腔镜切除肝脏时识别肝血管的手术内人工智能系统:一项回顾性实验研究

Norikazu Une^1,2, Shin Kobayashi¹, Daichi Kitaguchi²

¹Department of Hepatobiliary and Pancreatic Surgery, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.

Surgical endoscopy

|January 12, 2024

概括

人工智能模型在腹腔镜肝切除 (LLR) 过程中准确地识别肝血管,为实时导航系统提供了潜力. 2类模型在识别血管方面显示出更高的准确性,以改善外科指导.

科学领域:

医疗成像医学成像
手术技术手术技术
人工智能的人工智能

背景情况:

精确的肝血管识别对于安全有效的腹腔镜肝切除 (LLR) 是至关重要的.
目前的方法依赖于外科医生的专业知识,突出需要先进的可视化工具.
本研究探讨了人工智能在LLR期间增强船舶识别方面的作用.

研究的目的:

开发和评估人工智能 (AI) 模型,用于识别LLR中的肝血管.
评估这些AI模型的准确性和实时性能.
探索AI在为LLR创建自动导航系统方面的潜力.

主要方法:

使用特征金字塔网络架构开发了两个AI模型 (2类和3类),用于肝血管的语义细分.
模型在48个LLR视频剪辑中的2421上接受了训练,肝脏静脉和格里索纳脚被标记.
模型的性能是使用子系数 (DC) 和十名外科医生的定性评估来评估的.

主要成果:

2类人工智能模型实现了0.789的平均子系数 (DC),处理速度为0.094秒.
3类AI模型显示较低的平均直流值 (0.631为肝静脉,0.482为Glissonean pedicles),处理时间为0.097秒.
外科医生的定性评估表明,2类模型在血管识别方面表现良好.

结论:

深度学习模型已成功开发,用于在LLR过程中高准确度和速度识别肝血管.
这些发现表明实时自动导航系统的可行性,以帮助外科医生在LLR期间.
人工智能驱动的血管识别有望提高腹腔镜肝脏手术的安全性和效率.

关键词:

人工智能的人工智能是人工智能.计算机辅助手术是计算机辅助的手术.深度学习是一种深度学习.在操作内部识别.腹腔镜切除肝脏的切除方法语义细分语义细分是指语义细分.

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