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Differentiation of thyroid nodules on US using features learned and extracted from various convolutional neural networks

Authors
 Eunjung Lee  ;  Heonkyu Ha  ;  Hye Jung Kim  ;  Hee Jung Moon  ;  Jung Hee Byon  ;  Sun Huh  ;  Jinwoo Son  ;  Jiyoung Yoon  ;  Kyunghwa Han  ;  Jin Young Kwak 
Citation
 SCIENTIFIC REPORTS, Vol.9(1) : 19854, 2019 
Journal Title
 SCIENTIFIC REPORTS 
Issue Date
2019
Abstract
Thyroid nodules are a common clinical problem. Ultrasonography (US) is the main tool used to sensitively diagnose thyroid cancer. Although US is non-invasive and can accurately differentiate benign and malignant thyroid nodules, it is subjective and its results inevitably lack reproducibility. Therefore, to provide objective and reliable information for US assessment, we developed a CADx system that utilizes convolutional neural networks and the machine learning technique. The diagnostic performances of 6 radiologists and 3 representative results obtained from the proposed CADx system were compared and analyzed.
Files in This Item:
T201905358.pdf Download
DOI
10.1038/s41598-019-56395-x
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
5. Research Institutes (연구소) > Others (기타) > 1. Journal Papers
Yonsei Authors
Kwak, Jin Young(곽진영) ORCID logo https://orcid.org/0000-0002-6212-1495
Moon, Hee Jung(문희정) ORCID logo https://orcid.org/0000-0002-5643-5885
Han, Kyung Hwa(한경화)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/174708
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