Deep Learning for the Detection, Localization, and Characterization of Focal Liver Lesions on Abdominal US Images-Reference-Cited by-同舟云学术

Deep Learning for the Detection, Localization, and Characterization of Focal Liver Lesions on Abdominal US Images

Published:2022-05-01 Issue:3 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Dadoun Hind^ORCID,Rousseau Anne-Laure,de Kerviler Eric^ORCID,Correas Jean-Michel^ORCID,Tissier Anne-Marie^ORCID,Joujou Fanny,Bodard Sylvain,Khezzane Kemel,de Margerie-Mellon Constance^ORCID,Delingette Hervé,Ayache Nicholas

Funder

National Research Agency

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.210110

Reference19 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

2. Tumour evolution in hepatocellular carcinoma

3. ACG Clinical Guideline: The Diagnosis and Management of Focal Liver Lesions

4. Perceived barriers in the use of ultrasound in developing countries

5. Early detection and curative treatment of hepatocellular carcinoma: A cost-effectiveness analysis in France and in the United States

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