AIMC Topic: Thyroid Nodule
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Utilizing machine learning for early screening of thyroid nodules: a dual-center cross-sectional study in China.
Frontiers in endocrinology
Jun 14, 2024
BACKGROUND: Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformation. Early screening is crucial for management, yet current models focus mainly on ultrasound features. This study explores machine learning for screeni...
Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in China.
The Lancet. Digital health
Jun 6, 2024
BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by t...
Classification of Benign-Malignant Thyroid Nodules Based on Hyperspectral Technology.
Sensors (Basel, Switzerland)
May 17, 2024
In recent years, the incidence of thyroid cancer has rapidly increased. To address the issue of the inefficient diagnosis of thyroid cancer during surgery, we propose a rapid method for the diagnosis of benign and malignant thyroid nodules based on h...
Hybrid deep learning assisted multi classification: Grading of malignant thyroid nodules.
International journal for numerical methods in biomedical engineering
May 12, 2024
Thyroid nodules are commonly diagnosed with ultrasonography, which includes internal characteristics, varying looks, and hazy boundaries, making it challenging for a clinician to differentiate between malignant and benign forms based only on visual i...
A fully autonomous robotic ultrasound system for thyroid scanning.
Nature communications
May 11, 2024
The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasou...
Machine learning to predict the occurrence of thyroid nodules: towards a quantitative approach for judicious utilization of thyroid ultrasonography.
Frontiers in endocrinology
May 7, 2024
INTRODUCTION: Ultrasound is instrumental in the early detection of thyroid nodules, which is crucial for appropriate management and favorable outcomes. However, there is a lack of clinical guidelines for the judicious use of thyroid ultrasonography i...
Enhanced thyroid nodule segmentation through U-Net and VGG16 fusion with feature engineering: A comprehensive study.
Computer methods and programs in biomedicine
May 3, 2024
BACKGROUND AND OBJECTIVE: The thyroid gland, a key component of the endocrine system, is pivotal in regulating bodily functions. Thermography, a non-invasive imaging technique utilizing infrared cameras, has emerged as a diagnostic tool for thyroid-r...
Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos.
IEEE transactions on medical imaging
May 2, 2024
Deep learning techniques have been investigated for the computer-aided diagnosis of thyroid nodules in ultrasound images. However, most existing thyroid nodule detection methods were simply based on static ultrasound images, which cannot well explore...
The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.
Scientific reports
Apr 3, 2024
Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporti...
Localization and Risk Stratification of Thyroid Nodules in Ultrasound Images Through Deep Learning.
Ultrasound in medicine & biology
Mar 16, 2024
OBJECTIVE: Deep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. The aim of the study described here was to develop an integrated system that combines a deep learning model and a...
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