Evaluating the Performance of a Convolutional Neural Network Algorithm for Measuring Thoracic Aortic Diameters in a Heterogeneous Population-Reference-Cited by-同舟云学术

Evaluating the Performance of a Convolutional Neural Network Algorithm for Measuring Thoracic Aortic Diameters in a Heterogeneous Population

Published:2022-03-01 Issue:2 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Monti Caterina B.^ORCID,van Assen Marly^ORCID,Stillman Arthur E.^ORCID,Lee Scott J.^ORCID,Hoelzer Philipp^ORCID,Fung George S. K.^ORCID,Secchi Francesco^ORCID,Sardanelli Francesco^ORCID,De Cecco Carlo N.^ORCID

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210196

Reference10 articles.

1. Thoracic Aortic Aneurysm and Dissection

2. Clinical characteristics of aortic aneurysm and dissection as a cause of sudden death in outpatients

3. 2010 ACCF/AHA/AATS/ACR/ASA/SCA/SCAI/SIR/STS/SVM Guidelines for the Diagnosis and Management of Patients With Thoracic Aortic Disease

4. Artificial intelligence in radiology

5. A hybrid method based on level set and 3D region growing for segmentation of the thoracic aorta

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