人工智能在处理大数据、复杂非确定性数据、深入挖掘数据潜在信息等方面有着超越人类的优势。医学影像数据包含丰富的人体健康信息，是医生做出医学诊断的重要依据。面对复杂的医学影像信息和持续增长的医学影像诊断需求，医生人工影像解读暴露出的易受主观认知影响、效率低且误诊率高等诸多缺点愈加明显。本文从人工智能技术特点出发，结合具体病症分析人工智能在人体结构、病灶区的分割，疾病的早期诊断，解剖结构、病灶区的检测等方面的研究成果，最后总结现阶段人工智能在医学影像诊断中尚存在的问题，包括诊断结果可解释性差、医学数据量少及系统性评估标准缺失等，并进一步分析未来人工智能在医学影像诊断中的发展方向。

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