Deep Learning for COVID Image Analysis |
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| Editor:
| Greenspan, Hayit
Zhou, S. Kevin |
| Series title: | The MICCAI Society Book Ser. |
| ISBN: | 978-0-323-90107-9 |
| Publication Date: | Jan 2029 |
| Publisher: | Elsevier Science & Technology
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| Imprint: | Academic Press |
| Book Format: | Paperback |
| List Price: | USD $125.00 |
Book Description:
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Deep Learning for COVID Image Analysis provides a comprehensive overview of the most recently developed deep learning-based systems and solutions for COVID-19 image analysis, assembling a collection of state-of-the-art works for detection, severity analysis and predictive analysis, all of which are tools that support handling of the disease. The extraordinarily rapid spread of this pandemic has demonstrated that a new disease entity with a subset of relatively unique...
More Description
Deep Learning for COVID Image Analysis provides a comprehensive overview of the most recently developed deep learning-based systems and solutions for COVID-19 image analysis, assembling a collection of state-of-the-art works for detection, severity analysis and predictive analysis, all of which are tools that support handling of the disease. The extraordinarily rapid spread of this pandemic has demonstrated that a new disease entity with a subset of relatively unique characteristics can pose a major new clinical challenge that requires new diagnostic tools in imaging.
The AI/Deep Learning Imaging community has shown in many recent publications that rapidly developed AI-based automated CT and Xray image analysis tools can achieve high accuracy in the detection of Coronavirus positive patients as well as quantifying the disease burden.