A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging

被引:2
|
作者
Mervak, Benjamin M. [1 ]
Fried, Jessica G. [1 ]
Wasnik, Ashish P. [1 ]
机构
[1] Univ Michigan, Michigan Med, Dept Radiol, 1500 E Med Ctr Dr, Ann Arbor, MI 48109 USA
关键词
artificial intelligence; machine learning; deep learning; radiology; abdominal imaging; body imaging; MRI; CT; US; COMPUTED-TOMOGRAPHY; SEGMENTATION; CANCER; CT; RADIOLOGY; SARCOPENIA; CARCINOMA; DIAGNOSIS; IMAGES; RISK;
D O I
10.3390/diagnostics13182889
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has been increasing, with more than 30 FDA-approved algorithms now available for applications in the abdomen and pelvis. In this manuscript, we explore some of the fundamentals of artificial intelligence and machine learning, review major functions that AI algorithms may perform, introduce current and potential future applications of AI in abdominal imaging, provide a basic understanding of the pathways by which AI algorithms can receive FDA approval, and explore some of the challenges with the implementation of AI in clinical practice.
引用
收藏
页数:13
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