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人工智能在肝脏医学影像中的应用。

Artificial intelligence in medical imaging of the liver.

机构信息

Sino-German Tongji-Caritas Research Center of Ultrasound in Medicine, Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.

Department of Ultrasound, Tianyou Hospital Affiliated to Wuhan University of Technology, Wuhan 430030, Hubei Province, China.

出版信息

World J Gastroenterol. 2019 Feb 14;25(6):672-682. doi: 10.3748/wjg.v25.i6.672.

Abstract

Artificial intelligence (AI), particularly deep learning algorithms, is gaining extensive attention for its excellent performance in image-recognition tasks. They can automatically make a quantitative assessment of complex medical image characteristics and achieve an increased accuracy for diagnosis with higher efficiency. AI is widely used and getting increasingly popular in the medical imaging of the liver, including radiology, ultrasound, and nuclear medicine. AI can assist physicians to make more accurate and reproductive imaging diagnosis and also reduce the physicians' workload. This article illustrates basic technical knowledge about AI, including traditional machine learning and deep learning algorithms, especially convolutional neural networks, and their clinical application in the medical imaging of liver diseases, such as detecting and evaluating focal liver lesions, facilitating treatment, and predicting liver treatment response. We conclude that machine-assisted medical services will be a promising solution for future liver medical care. Lastly, we discuss the challenges and future directions of clinical application of deep learning techniques.

摘要

人工智能(AI),特别是深度学习算法,在图像识别任务中表现出色,引起了广泛关注。它们可以自动对复杂的医学图像特征进行定量评估,并以更高的效率实现更高的诊断准确性。AI 在肝脏的医学影像学中得到了广泛的应用和日益普及,包括放射学、超声和核医学。AI 可以帮助医生做出更准确和可重复的影像学诊断,同时减轻医生的工作量。本文介绍了 AI 的基本技术知识,包括传统的机器学习和深度学习算法,特别是卷积神经网络,以及它们在肝脏疾病的医学影像学中的临床应用,例如检测和评估局灶性肝病变,辅助治疗以及预测肝脏治疗反应。我们得出结论,机器辅助医疗服务将是未来肝脏医疗保健的一个有前途的解决方案。最后,我们讨论了深度学习技术临床应用的挑战和未来方向。

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Artificial intelligence in radiology.人工智能在放射学中的应用。
Nat Rev Cancer. 2018 Aug;18(8):500-510. doi: 10.1038/s41568-018-0016-5.
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Deep learning for staging liver fibrosis on CT: a pilot study.深度学习在 CT 上分期肝纤维化:一项初步研究。
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Is pathology prepared for the adoption of artificial intelligence?病理学为采用人工智能做好准备了吗?
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