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人工智能正在深刻改变医学影像学的全流程,覆盖了从疾病筛查、智能诊断到风险分层和临床决策支持的各个环节,展现出巨大的临床应用价值。随着计算能力的提升和算法的快速发展,深度学习、生成模型以及Transformer等先进方法已在神经系统和头颈、胸部、腹部、心血管、乳腺及骨肌系统等多个领域得到广泛应用,并在病灶自动分割、疾病精准分类、预后风险预测等方面取得了突破性进展,不仅提升了影像解读的效率与准确性,也推动了个体化医疗的发展。本文将基于解剖学分类的视角,系统梳理人工智能在医学影像中的典型应用场景,重点阐述其在不同系统疾病诊治中的优势与挑战,并进一步探讨当前临床研究与转化应用的最新进展及未来发展趋势。
Abstract:Artificial intelligence(AI) is transforming the entire workflow of medical imaging spanning disease screening, intelligent diagnosis, risk stratification and clinical decision support, with significant clinical utility. Advances in computational power and algorithmic development-particularly in deep learning, generative models, and Transformer-based architectures have led to their widespread adoption across multiple anatomical domains, including neurological, head and neck, thoracic, abdominal, cardiovascular, breast and musculoskeletal imaging. These technologies have achieved breakthroughs in automated lesion segmentation, disease classification, and prognostic prediction, thereby enhancing the efficiency and accuracy of image interpretation while also facilitating personalized medicine. From an anatomical perspective, this review examined key applications of AI in medical imaging, highlighted its benefits and challenges across various disease contexts, and discussed recent clinical advances and future directions in translational implementation.
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基本信息:
DOI:10.13885/j.issn.2097-681X.2025.07.001
中图分类号:TP18;R445
引用信息:
[1]赵文哲,刘军.人工智能驱动医学影像精准诊疗:多系统临床应用与转化的进展和挑战[J].兰州大学学报(医学版),2025,51(07):1-8.DOI:10.13885/j.issn.2097-681X.2025.07.001.
基金信息:
陕西省重点研发计划资助项目(2025CY-YBXM-196)