肝癌的外科治疗正经历从传统经验范式向数字化、智能化精准模式的深刻变革。微创肝切除术（MILR）虽已广泛应用，但在复杂脉管解剖与深度感知方面仍面临挑战。人工智能（AI）技术的参与将给微创外科围手术期管理带来重大影响。术前规划阶段，通过深度学习实现脉管与胆道结构的快速量化重建，结合影像组学与可解释AI模型精准预判未来残余肝体积及术后肝衰竭风险。术中辅助阶段，导航技术经历了从“静态核准”到“智能自适应配准”的演进，特别是“脑-眼-手”协同的机器人智慧手术体系及器械“去遮挡”技术的应用，显著提升了复杂部位肿瘤切除的精度。术后监测阶段，AI推动了从被动随访向主动实时监测的转型。尽管在形变补偿精度与算法泛化性方面仍存在瓶颈，但AI驱动的“数据驱动”范式必将引领微创外科迈向全流程无缝化的智能化新时代。

The surgical treatment of hepatocellular carcinoma (HCC) is undergoing a profound paradigm shift from traditional empirical models to digital and intelligent precision medicine. While minimally invasive liver resection (MILR) is widely accepted, it still faces challenges in complex vascular anatomy and depth perception. The participation of artificial intelligence (AI) technology will have a significant impact on perioperative management in MILR. In the preoperative phase, deep learning enables rapid quantitative reconstruction of vascular and biliary structures, combined with radiomics and explainable AI models to predict future liver remnant and the risk of post-hepatectomy liver failure. During the intraoperative phase, navigation technology has evolved from "static calibration" to "intelligent adaptive registration." Notably, the robotic "Brain-Eye-Hand" collaborative system and instrument deocclusion technology have significantly enhanced the precision of resecting tumors in complex locations. Postoperatively, AI promotes the transition from passive follow-up to active real-time monitoring. Despite existing bottlenecks in deformation compensation accuracy and algorithmic generalizability, the AI-driven "data-driven" paradigm will lead minimally invasive surgery into a new era of seamless, full-process intelligence.