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Published on: December 19, 2020
Perspective of AI system for COVID-19 detection using chest images: a review
Dolly Das1, Saroj Kumar Biswas1, Sivaji Bandyopadhyay1
1Department of Computer Science and Engineering, National Institute of Technology Silchar, Assam Silchar, Cachar, India.
Insights
This study reviews chest imaging features for detecting Coronavirus Disease 2019 (COVID-19). Machine learning and deep learning algorithms analyze CT scans and X-rays for faster, reliable COVID-19 diagnosis.
Area of Science:
- Medical Imaging
- Artificial Intelligence in Medicine
- Infectious Diseases
Background:
- Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2, presents diagnostic challenges due to its varied symptoms and resemblance to other pneumonias.
- Current diagnostic methods like RT-PCR can be unreliable or unavailable, necessitating alternative approaches.
- The zoonotic origin and rapid global spread of SARS-CoV-2 underscore the need for efficient diagnostic tools.
Purpose of the Study:
- To identify and review key features in chest X-ray (CXR) and CT scans indicative of COVID-19.
- To explore the application of Machine Learning (ML) and Deep Learning (DL) for analyzing chest images in COVID-19 detection.
- To compare the effectiveness of ML and DL approaches in diagnosing COVID-19 using medical imaging.
Main Methods:
- Review of scientific literature on chest imaging features associated with COVID-19.
- Analysis of studies employing ML and DL algorithms for COVID-19 detection from CXR and CT images.
- Comparative assessment of different ML and DL models and their performance metrics.
Main Results:
- Chest imaging, particularly CT scans, reveals characteristic patterns that can aid in COVID-19 diagnosis.
- ML and DL models demonstrate potential for accurate and rapid COVID-19 detection from chest images.
- Various algorithms show promise, with performance varying based on the dataset and model architecture.
Conclusions:
- Chest imaging analysis, enhanced by ML and DL, offers a viable alternative or adjunct to RT-PCR for COVID-19 diagnosis.
- Further research and validation of AI-driven imaging analysis are crucial for clinical implementation.
- These advanced techniques can improve diagnostic speed and reliability, especially during pandemics.
Abstract:
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.
