Combination of Active Transfer Learning and Natural Language Processing to Improve Liver Volumetry Using Surrogate Metrics with Deep Learning-Reference-Cited by-同舟云学术

Combination of Active Transfer Learning and Natural Language Processing to Improve Liver Volumetry Using Surrogate Metrics with Deep Learning

Published:2019-01 Issue:1 Volume:1 Page:e180019
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Marinelli Brett¹,Kang Martin¹,Martini Michael¹^ORCID,Zech John R.¹,Titano Joseph¹,Cho Samuel¹,Costa Anthony B.¹,Oermann Eric K.¹

Affiliation:

1. From the Departments of Radiology (B.M., M.K., M.M., J.T.), Orthopedic Surgery (S.C.), and Neurological Surgery (A.B.C., E.K.O.), Mount Sinai Health System, 1468 Madison Ave, Annenberg Building, 8th Floor, New York, NY 10029; and Department of Medicine, California Pacific Medical Center, San Francisco, Calif (J.R.Z.).

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.2019180019

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5. Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets

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