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

Artificial intelligence in medical imaging of the liver

Li-Qiang Zhou  1 , Jia-Yu Wang  1 , Song-Yuan Yu  2 , Ge-Ge Wu  1 , Qi Wei  1 , You-Bin Deng  1 , Xing-Long Wu  3 , Xin-Wu Cui  4 , Christoph F Dietrich  1
Affiliations
Review

Artificial intelligence in medical imaging of the liver

Li-Qiang Zhou et al. World J Gastroenterol. .

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.

Keywords: Artificial intelligence; Deep learning; Imaging; Liver; Machine learning; Ultrasound.

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Conflict of interest statement

Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors who contributed their efforts in this manuscript.

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