Background Ultrasound (US) is widely used in the clinical diagnosis of thyroid nodules.
Artificial intelligence-powered US is becoming an important issue in the research …

Purpose This study aimed to train and validate deep learning (DL) models for differentiating
malignant from benign thyroid nodules on US images and compare their performance with …

Background To explore the ability of the deep learning network Inception-v3 to differentiate
between papillary thyroid carcinomas (PTCs) and benign nodules in ultrasound images …

Ultrasonography with fine-needle aspiration biopsy is commonly used to detect thyroid
cancer. However, thyroid ultrasonography is prone to subjective interpretations and …

With many thyroid nodules being incidentally detected, it is important to identify as many
malignant nodules as possible while excluding those that are highly likely to be benign from …

The purpose of this study was to evaluate and compare the diagnostic performances of the
deep convolutional neural network (CNN) and expert radiologists for differentiating thyroid …

Automated thyroid nodule classification in ultrasound images is an important way to detect
thyroid nodules and to make a more accurate diagnosis. In this paper, we propose a novel …

Ultrasonography is a common modality for diagnosing thyroid nodules. Computer-aided
classification of benign and malignant thyroid nodules in the ultrasound images is …

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 …

Objective The aim of this study is to develop a model using Deep Neural Network (DNN) to
diagnose thyroid nodules in patients with Hashimoto's Thyroiditis. Methods In this …