胡颖颖,雷志毅

肺空洞性疾病是一类常见且复杂的肺部疾病，指肺部组织坏死液化后，经由支气管排出，并引入空气形成，其常见病因包括肺结核、肺癌、肺脓肿及肺转移瘤等。目前，X线及CT已广泛应用于肺空洞性疾病治疗的影像学评估中，然而各类空洞的临床表现和影像学特征有相当大的交叉和重叠，使得其诊断和鉴别变得尤为困难，此外，庞大的影像资料需要影像科医师付出大量精力判读，在一定程度上不可避免的增加了漏诊、误诊可能。近年来，人工智能（AI）的快速发展为解决这些问题提供了新的思路和方法。本文综述了AI在肺空洞性疾病诊断中的最新研究进展，探讨了AI的基本原理及其在影像分析中的应用实例，强调其在临床应用中的潜力和未来发展方向，以期为相关领域的研究者和临床工作者提供有价值的参考和启示。

人工智能；肺空洞性疾病；影像组学；深度学习；诊断进展

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