AIMC Topic: Thyroid Neoplasms

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Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study.

The Lancet. Oncology
BACKGROUND: The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth is especially driven by increased diagn...

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

AJR. American journal of roentgenology
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of substantial radiation exposure and the use of contrast material (CM). The purpose of this article i...

Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches.

Journal of healthcare engineering
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime import...

The usefulness of fine-needle aspirates for detection of recurrent carcinoma in the thyroid bed.

Journal of the American Society of Cytopathology
INTRODUCTION: Locoregional recurrence of thyroid carcinoma has a negative impact on patient prognosis. In the current study, we retrospectively reviewed cases of thyroid bed lesions in the last 3 years, correlating cytologic diagnoses with clinical f...

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Diagnostic cytopathology
BACKGROUND: To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem.

Differentiation of the Follicular Neoplasm on the Gray-Scale US by Image Selection Subsampling along with the Marginal Outline Using Convolutional Neural Network.

BioMed research international
We conducted differentiations between thyroid follicular adenoma and carcinoma for 8-bit bitmap ultrasonography (US) images utilizing a deep-learning approach. For the data sets, we gathered small-boxed selected images adjacent to the marginal outlin...

Prediction of dose to the relatives of patients treated with radioiodine-131 using neural networks.

Journal of radiological protection : official journal of the Society for Radiological Protection
In this study, the effective dose received by the family members and caregivers of 52 thyroid cancer patients, who had been treated with radioiodine I-131, was measured to investigate the ability of the neural network to predict the doses to the rela...

A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment.

Thyroid : official journal of the American Thyroid Association
BACKGROUND: An initial clinical assessment is described of a new, commercially available, computer-aided diagnosis (CAD) system using artificial intelligence (AI) for thyroid ultrasound, and its performance is evaluated in the diagnosis of malignant ...