Deep learning for the diagnosis of suspicious thyroid nodules based on multimodal ultrasound images
出版年份 2022 全文链接
标题
Deep learning for the diagnosis of suspicious thyroid nodules based on multimodal ultrasound images
作者
关键词
-
出版物
Frontiers in Oncology
Volume 12, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2022-11-08
DOI
10.3389/fonc.2022.1012724
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Deep convolutional neural network for classification of thyroid nodules on ultrasound: Comparison of the diagnostic performance with that of radiologists
- (2022) Yeon-Jae Kim et al. EUROPEAN JOURNAL OF RADIOLOGY
- Artificial Intelligence for Thyroid Nodule Characterization: Where Are We Standing?
- (2022) Salvatore Sorrenti et al. Cancers
- Thyroid nodule recognition using a joint convolutional neural network with information fusion of ultrasound images and radiofrequency data
- (2021) Zhong Liu et al. EUROPEAN RADIOLOGY
- Deep Learning Based on ACR TI-RADS Can Improve the Differential Diagnosis of Thyroid Nodules
- (2021) Ge-Ge Wu et al. Frontiers in Oncology
- The Role of CEUS in the Evaluation of Thyroid Cancer: From Diagnosis to Local Staging
- (2021) Salvatore Sorrenti et al. Journal of Clinical Medicine
- Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images
- (2020) Hui Zhou et al. EUROPEAN JOURNAL OF RADIOLOGY
- Variability in the interpretation of grey-scale ultrasound features in assessing thyroid nodules: A systematic review and meta-analysis
- (2020) Huan Liu et al. EUROPEAN JOURNAL OF RADIOLOGY
- Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology
- (2020) Soon Woo Kwon et al. JOURNAL OF DIGITAL IMAGING
- A Clinical Assessment of an Ultrasound Computer-Aided Diagnosis System in Differentiating Thyroid Nodules With Radiologists of Different Diagnostic Experience
- (2020) Yichun Zhang et al. Frontiers in Oncology
- Diagnostic value of multimodal ultrasound imaging in differentiating benign and malignant TI-RADS category 4 nodules
- (2019) Shufang Pei et al. International Journal of Clinical Oncology
- A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence–Powered Ultrasound for Improving Clinical Workflow
- (2019) Zeynettin Akkus et al. Journal of the American College of Radiology
- TIRADS score is of limited clinical value for risk stratification of indeterminate cytological results
- (2018) E Chaigneau et al. EUROPEAN JOURNAL OF ENDOCRINOLOGY
- Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study
- (2018) Kun Wang et al. GUT
- US Fine-Needle Aspiration Biopsy for Thyroid Malignancy: Diagnostic Performance of Seven Society Guidelines Applied to 2000 Thyroid Nodules
- (2018) Eun Ju Ha et al. RADIOLOGY
- Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study
- (2018) Xiangchun Li et al. LANCET ONCOLOGY
- Intraobserver and Interobserver Variability in Ultrasound Measurements of Thyroid Nodules
- (2017) Hyung Jin Lee et al. JOURNAL OF ULTRASOUND IN MEDICINE
- Risk Stratification of Thyroid Nodules on Ultrasonography: Current Status and Perspectives
- (2017) Eun Ju Ha et al. THYROID
- Computer-aided assessment of regional vascularity of thyroid nodules for prediction of malignancy
- (2017) Faisal N. Baig et al. Scientific Reports
- ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee
- (2017) Franklin N. Tessler et al. Journal of the American College of Radiology
- Cancer statistics in China, 2015
- (2016) Wanqing Chen et al. CA-A CANCER JOURNAL FOR CLINICIANS
- 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) Bryan R. Haugen et al. THYROID
- Ultrasound-Based Risk Stratification for Malignancy in Thyroid Nodules: A Four-Tier Categorization System
- (2015) Hyobin Seo et al. EUROPEAN RADIOLOGY
- Thyroid cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
- (2012) F. Pacini et al. ANNALS OF ONCOLOGY
- Thyroid Imaging Reporting and Data System for US Features of Nodules: A Step in Establishing Better Stratification of Cancer Risk
- (2011) Jin Young Kwak et al. RADIOLOGY
- Observer variability in the sonographic evaluation of thyroid nodules
- (2010) Chang Suk Park et al. JOURNAL OF CLINICAL ULTRASOUND
- A prospective study evaluating the accuracy of using combined clinical factors and candidate diagnostic markers to refine the accuracy of thyroid fine needle aspiration biopsy
- (2010) Aarti Mathur et al. SURGERY
- The Bethesda Thyroid Fine-Needle Aspiration Classification System: Year 1 at an Academic Institution
- (2009) Constantine G.A. Theoharis et al. THYROID
- Interobserver and Intraobserver Variations in Ultrasound Assessment of Thyroid Nodules
- (2009) Seon Hyeong Choi et al. THYROID
- US-Elastography in the Differential Diagnosis of Benign and Malignant Thyroid Nodules
- (2008) Carmela Asteria et al. THYROID
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