Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening

• 作者: Cao Xue-Fang Li Yuan Xin He-Nan Zhang Hao-Ran Pai Madhukar Gao Lei
• 来源期刊: 慢性疾病与转化医学（英文）
• 关键词: Tuberculosis Artificial intelligence Digital chest radiography Diagnosis Triage
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Perspective
• 页码范围: 35-40
• 页数: 6页
• 语种: 中文
• DOI: 10.1016/j.cdtm.2021.02.001

摘要

Currently, the diagnosis of tuberculosis (TB) is mainly based on the comprehensive consideration of the patient's symptoms and signs, laboratory examinations and chest radiography (CXR). CXR plays a pivotal role to support the early diagnosis of TB, especially when used for TB screening and differential diagnosis. However, high cost of CXR hardware and shortage of certified radiologists poses a major challenge for CXR application in TB screening in resource limited settings. The latest development of artificial intelligence (AI) combined with the accumulation of a large number of medical images provides new opportunities for the establishment of computer-aided detection (CAD) systems in the medical applications, especially in the era of deep learning (DL) technology. Several CAD solutions are now commercially available and there is growing evidence demonstrate their value in imaging diagnosis. Recently, WHO published a rapid communication which stated that CAD may be used as an alternative to human reader interpretation of plain digital CXRs for screening and triage of TB.