Background 99m Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for
evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively …

Objectives The aim of this study was to improve the diagnostic performance of nuclear
medicine physicians using a deep convolutional neural network (DCNN) model and validate …

Objective To construct deep learning (DL) models to improve the accuracy and efficiency of
thyroid disease diagnosis by thyroid scintigraphy. Methods We constructed DL models with …

Thyroid scintigraphy is an important investigation for the clinical diagnosis of thyroid
diseases. Thyroid diseases often present characteristic abnormal patterns in scintigraphic …

Although thyroid ultrasonography (US) has been widely applied, it is still difficult to
distinguish benign and malignant nodules. Currently, convolutional neural network (CNN) …

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 …

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 …

Abstract Background and Objective: As one of the largest endocrine organs in the human
body, the thyroid gland regulates daily metabolism. Early detection of thyroid disease leads …

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 …

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 …