COVID-19 Pneumonia : Basics of Radiological Evaluation and State of the Art Artificial Intelligence for Management
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- OHNO Yoshiharu
- Department of Radiology, Fujita Health University School of Medicine Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
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- AOYAGI Kota
- Canon Medical Systems Corporation
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- ARAKITA Kazumasa
- Canon Medical Systems Corporation
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- HAMABUCHI Nayu
- Department of Radiology, Fujita Health University School of Medicine
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- TAKAHASHI Kazuya
- Department of Radiology, Fujita Health University School of Medicine
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- FUJISAWA Reina
- Department of Radiology, Fujita Health University School of Medicine
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- TANAKA Yumi
- Department of Radiology, Fujita Health University School of Medicine
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- HANAMATSU Satomu
- Department of Radiology, Fujita Health University School of Medicine
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- SHIGEMURA Chika
- Department of Radiology, Fujita Health University School of Medicine
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- WATANABE Ayumi
- Department of Radiology, Fujita Health University School of Medicine
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- HATTORI Hidekazu
- Department of Radiology, Fujita Health University School of Medicine
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- MURAYAMA Kazuhiro
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
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- TOYAMA Hiroshi
- Department of Radiology, Fujita Health University School of Medicine
Bibliographic Information
- Other Title
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- COVID-19肺炎の画像診断における基礎とAI画像解析の現状と将来展望
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Abstract
<p>COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic in all over the world. Since then, many investigators have trying to determine its' epidemiology, etiology,pathophysiology, radiological manifestations, therapeutic strategies and outcome prediction, etc. In addition, a few academic societies as well as academic institution had proposed some category classifications for assessing COVID-19 pneumonia,and many clinicians reported their utility in routine clinical practice. Moreover, artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID-19 pandemic, when considering the above-mentioned situation in Chest Radiology. For present purposes, AI can currently be tried to demonstrate its' clinical utility for diagnosis, disease severity evaluation and treatment response assessment for radiological examination in patients with COVID-19 infection. Then,many papers have been reported radiological features as well as clinical features of COVID-19 infection, development, and clinical application of AI system for chest radiograph (or chest X-ray : CXR) or computed tomography (CT) in not only China, but also other Western countries including Japan and Korea. Encouraging for developments and clinical studies for AI may contribute to not only clinicians, but also radiologists for improving clinical practice in patients with COVID-19 infection. Moreover, AI is required a careful balance between data privacy and public health concerns, and more rigorous human-AI interaction. So, the progress of AI is very important for future control of COVID-19 infection in routine clinical practice. <br> In this article, we discuss 1) radiological manifestation of COVID-19 pneumonia on CXR or CT, 2) current clinical indication for CT examination in suspected COVID-19 patients, 3) previously published categorization for probability of COVID-19 pneumonia on CT (or CXR) by a few academic societies or institutions and 4) current status and future direction of AI for radiological assessment in patients with COVID-19.</p>
Journal
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- Medical Imaging and Information Sciences
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Medical Imaging and Information Sciences 38 (1), 1-7, 2021-03-29
MEDICAL IMAGING AND INFORMATION SCIENCES
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Details 詳細情報について
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- CRID
- 1390006050800347520
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- NII Article ID
- 130008006414
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- ISSN
- 18804977
- 09101543
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed