[HTML][HTML] 2021 Korean thyroid imaging reporting and data system and imaging-based management of thyroid nodules: Korean Society of Thyroid Radiology consensus …

EJ Ha, SR Chung, DG Na, HS Ahn… - Korean journal of …, 2021 - ncbi.nlm.nih.gov
Incidental thyroid nodules are commonly detected on ultrasonography (US). This has
contributed to the rapidly rising incidence of low-risk papillary thyroid carcinoma over the last …

Performance of five ultrasound risk stratification systems in selecting thyroid nodules for FNA

M Castellana, C Castellana, G Treglia… - The Journal of …, 2020 - academic.oup.com
Context Ultrasound (US) risk stratification systems (RSSs) have been developed to reduce
the number of unnecessary fine-needle aspiration procedures (FNA) in patients with thyroid …

2020 Chinese guidelines for ultrasound malignancy risk stratification of thyroid nodules: the C-TIRADS

JQ Zhou, LX Yin, X Wei, S Zhang, YY Song, BM Luo… - Endocrine, 2020 - Springer
Thyroid nodules are very common all over the world, and China is no exception. Ultrasound
plays an important role in determining the risk stratification of thyroid nodules, which is …

Management of thyroid nodules seen on US images: deep learning may match performance of radiologists

M Buda, B Wildman-Tobriner, JK Hoang, D Thayer… - Radiology, 2019 - pubs.rsna.org
Background Management of thyroid nodules may be inconsistent between different
observers and time consuming for radiologists. An artificial intelligence system that uses …

A generic deep learning framework to classify thyroid and breast lesions in ultrasound images

YC Zhu, A AlZoubi, S Jassim, Q Jiang, Y Zhang… - Ultrasonics, 2021 - Elsevier
Breast and thyroid cancers are the two common cancers to affect women worldwide.
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …

Challenges related to artificial intelligence research in medical imaging and the importance of image analysis competitions

LM Prevedello, SS Halabi, G Shih, CC Wu… - Radiology: Artificial …, 2019 - pubs.rsna.org
In recent years, there has been enormous interest in applying artificial intelligence (AI) to
radiology. Although some of this interest may have been driven by exaggerated …

Using artificial intelligence to revise ACR TI-RADS risk stratification of thyroid nodules: diagnostic accuracy and utility

B Wildman-Tobriner, M Buda, JK Hoang, WD Middleton… - Radiology, 2019 - pubs.rsna.org
Background Risk stratification systems for thyroid nodules are often complicated and
affected by low specificity. Continual improvement of these systems is necessary to reduce …

Update on ACR TI-RADS: Successes, Challenges, and Future Directions, From the AJR Special Series on Radiology Reporting and Data Systems

JK Hoang, WD Middleton… - American Journal of …, 2021 - Am Roentgen Ray Soc
The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-
RADS) is an ultrasound-based risk stratification system (RSS) for thyroid nodules that was …

Artificial intelligence in thyroid ultrasound

CL Cao, QL Li, J Tong, LN Shi, WX Li, Y Xu… - Frontiers in …, 2023 - frontiersin.org
Artificial intelligence (AI), particularly deep learning (DL) algorithms, has demonstrated
remarkable progress in image-recognition tasks, enabling the automatic quantitative …

Diagnosis of thyroid nodules: performance of a deep learning convolutional neural network model vs. radiologists

VY Park, K Han, YK Seong, MH Park, EK Kim… - Scientific reports, 2019 - nature.com
Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy
of thyroid ultrasound (US). We aimed to develop a deep learning-based US CAD system …