Artificial Intelligence in the Imaging of Diffuse Lung Disease - 04/10/22
Doi : 10.1016/j.rcl.2022.06.014
Jessica Chan, MD a, William F. Auffermann, MD, PhD b, ⁎ 
a Department of Radiology and Imaging Sciences, University of Utah Health, 30 North 1900 East, Room # 1A71, Salt Lake City, UT 84132, USA
b Interim Section Chief of Cardiothoracic Imaging, Department of Radiology and Imaging Sciences, University of Utah School of Medicine, University of Utah Health, 30 North 1900 East, Room # 1A71, Salt Lake City, UT 84132, USA
∗Corresponding author.
Resumen |
Diffuse lung diseases are a heterogeneous group of disorders that can be difficult to differentiate by imaging using traditional methods of evaluation. The overlap between various disorders results in difficulty when medical professionals attempt to interpret images. Artificial intelligence offers new tools for the evaluation and quantification of imaging of patients with diffuse lung disease.
El texto completo de este artículo está disponible en PDF.Keywords : Artificial intelligence, Interstitial lung disease, Computed tomography, Deep learning, Convolutional neural networks
Esquema
| Disclosures: None. |
© 2022
Elsevier Inc. Reservados todos los derechos.
Vol 60 - N° 6
P. 1033-1040 - novembre 2022 Regresar al número
Artículo precedente
- MR Imaging for the Evaluation of Diffuse Lung Disease : Where Are We?
- Bryan O'Sullivan-Murphy, Bastiaan Driehuys, Joseph Mammarappallil
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