Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology-Reference-Cited by-同舟云学术

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Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology

Published:2020-07-23 Issue:5 Volume:33 Page:1202-1208
ISSN:0897-1889
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Kwon Soon Woo,Choi Ik Joon,Kang Ju Yong,Jang Won Il,Lee Guk-Haeng,Lee Myung-Chul^ORCID

Funder

Korea Institute of Radiological and Medical Sciences funded by Ministry of Science and ICT

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

https://link.springer.com/content/pdf/10.1007/s10278-020-00362-w.pdf

Reference25 articles.

1. Sanabria A, Kowalski LP, Shah JP, Nixon IJ, Angelos P, Williams MD, Rinaldo A, Ferlito A: Growing incidence of thyroid carcinoma in recent years: factors underlying overdiagnosis. Head Neck 40:855-866,2018

2. Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE, Pacini Furio, Randolph GW, Sawka AM, Schlumberger M, Schuff KG, Sherman SI, Sosa JA, Steward DL, Tuttle RM, Wartofsky L: 2015 American Thyroid Association Management Guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer,2016

3. Kwak JY, Han KH, Yoon JH, Moon HJ, Son EJ, Park SH, Jung HK, Choi JS, Kim BM, Kim EK: Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk. Radiology 260:892-899,2011

4. Lingam RK, Qarib MH, Tolley NS: Evaluating thyroid nodules: predicting and selecting malignant nodules for fine-needle aspiration (FNA) cytology. Insights Imaging 4:617-624,2013

5. Choi YJ, Baek JH, Park HS, Shim WH, Kim TY, Shong YK, Lee JH: A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of thyroid nodules on ultrasound: initial clinical assessment. Thyroid 27:546-552, 2017

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1. Automatic Classification of Nodules from 2D Ultrasound Images Using Deep Learning Networks;Journal of Imaging;2024-08-22

2. A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging;Bioengineering;2024-06-25

3. Residual U-Net approach for thyroid nodule detection and classification from thyroid ultrasound images;Automatika;2024-02-26

4. QuCNet: Quantum-Inspired Convolutional Neural Networks for Optimized Thyroid Nodule Classification;IEEE Access;2024

5. AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions;Systems;2023-10-17

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