Improved detection of air trapping on expiratory computed tomography using deep learning.
<h4>Background</h4>Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited effi...
محفوظ في:
| المؤلفون الرئيسيون: | , , , , , , , , , , , , , , , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
Public Library of Science (PLoS)
2021-01-01
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| سلاسل: | PLoS ONE |
| الوصول للمادة أونلاين: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248902&type=printable |
| الوسوم: |
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