Artificial intelligence in gastrointestinal and hepatic imaging: past, present and future scopes

被引：1

作者：

Gandhi, Darshan ^{[1
,3
]}

Garg, Tushar ^{[2
,3
]}

Patel, Love ^{[3
,4
]}

Abou Elkassem, Asser ^{[3
,5
]}

Bansal, Varun ^{[3
,4
,6
,7
]}

Smith, Andrew ^{[3
,5
]}

机构：

[1] Univ Tennessee, Dept Diagnost Radiol, Hlth Sci Ctr, Memphis, TN 38103 USA

[2] Seth GS Med Coll, Dept Radiol, Acharya Donde Marg,Parel East,Parel, Mumbai 400012, Maharashtra, India

[3] Abbott NW Hosp, Div Hosp Med, Allina Hlth, Minneapolis, MN 55407 USA

[4] Univ Alabama Birmingham, Dept Radiol, 619,19th St South, Birmingham, AL 35249 USA

[5] Seth GS Med Coll, Acharya Donde Marg,Parel East,Parel, Mumbai 400012, Maharashtra, India

[6] King Edward Mem Hosp, Acharya Donde Marg,Parel East,Parel, Bombay 400012, Maharashtra, India

[7] King Edward Mem Hosp, Acharya Donde Marg,Parel East,Parel, Bombay 400012, Maharashtra, India

来源：

CLINICAL IMAGING | 2022年 / 87卷

关键词：

AI; Artificial intelligence; Machine learning; Deep learning; Hepatic; ABDOMINAL ORGAN SEGMENTATION; LOW-DOSE CT; COMPUTED-TOMOGRAPHY; NEURAL-NETWORK; LIVER SEGMENTATION; HIGH-QUALITY; RADIOLOGY; IMAGES; CLASSIFICATION; RECONSTRUCTION;

D O I：

10.1016/j.clinimag.2022.04.007

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

The use of technology in medicine has grown exponentially because of the technological advancements allowing the digitization of medical data and optimization of their processing to extract multiple features of significant clinical relevance. Radiology has benefited substantially from technical developments and innovations, such as artificial intelligence (AI). This article describes the subsets of AI methods relevant to gastrointestinal and hepatic imaging with examples. We also discuss the evolution of AI, the current challenges, and prospects for further development in the field.

引用

页码：43 / 53

页数：11

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