Das Dolly, Biswas Saroj Kumar, Bandyopadhyay Sivaji
Department of Computer Science and Engineering, National Institute of Technology Silchar, Assam Silchar, Cachar, India.
Multimed Tools Appl. 2022;81(15):21471-21501. doi: 10.1007/s11042-022-11913-4. Epub 2022 Mar 15.
Coronavirus Disease 2019 (COVID-19) is an evolving communicable disease caused due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has led to a global pandemic since December 2019. The virus has its origin from bat and is suspected to have transmitted to humans through zoonotic links. The disease shows dynamic symptoms, nature and reaction to the human body thereby challenging the world of medicine. Moreover, it has tremendous resemblance to viral pneumonia or Community Acquired Pneumonia (CAP). Reverse Transcription Polymerase Chain Reaction (RT-PCR) is performed for detection of COVID-19. Nevertheless, RT-PCR is not completely reliable and sometimes unavailable. Therefore, scientists and researchers have suggested analysis and examination of Computing Tomography (CT) scans and Chest X-Ray (CXR) images to identify the features of COVID-19 in patients having clinical manifestation of the disease, using expert systems deploying learning algorithms such as Machine Learning (ML) and Deep Learning (DL). The paper identifies and reviews various chest image features using the aforementioned imaging modalities for reliable and faster detection of COVID-19 than laboratory processes. The paper also reviews and compares the different aspects of ML and DL using chest images, for detection of COVID-19.
2019冠状病毒病（COVID-19）是一种由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的不断演变的传染病，自2019年12月以来已导致全球大流行。该病毒起源于蝙蝠，疑似通过人畜共患病传播给人类。这种疾病表现出动态症状、性质以及对人体的反应，从而给医学界带来了挑战。此外，它与病毒性肺炎或社区获得性肺炎（CAP）极为相似。通过逆转录聚合酶链反应（RT-PCR）来检测COVID-19。然而，RT-PCR并不完全可靠，有时也无法进行检测。因此，科学家和研究人员建议利用部署机器学习（ML）和深度学习（DL）等学习算法的专家系统，对计算机断层扫描（CT）和胸部X光（CXR）图像进行分析和检查，以识别出现该疾病临床表现的患者身上COVID-19的特征。本文利用上述成像方式识别并综述各种胸部图像特征，以便比实验室检测过程更可靠、更快速地检测COVID-19。本文还综述并比较了利用胸部图像检测COVID-19时ML和DL的不同方面。
